Effective Utterance Classification with Unsupervised Phonotactic Models
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作者: 张群
作者机构: 首都师范大学教育学院
出版物刊名: 世界教育信息
页码: 67-70页
年卷期: 2012年 第Z1期
主题词: 技术教育 技术教师 专业标准
摘要:NCATE机构是经美国教育部和高等教育认证委员会承认的职前教师认证权威机构,2008年NCATE发布了《为技术教育教师做准备的项目标准》,对技术教师的总体专业标准和23门学科项目标准作了详细的规定。
美国关于职前技术教育的做法对中国职前技术教育具有重要的借鉴作用,文章借此尝试提出改进我国技术教师培养的三点建议:注重职前教师的培养和认定,教师的学科知识和能力注重多元性、前沿性,注重培养技术教师的实践性。
人力资源词汇16PF 卡特尔16种人格因素测试360-degree appraisal 360度评估360-degree feedback 360度反馈7S 7S原则/模型New 7S 新7S原则/模型80/20 principle 80/20法则AAR-After Action Review 行动后学习机制Ability Test 能力测试Ability of Manager 管理者的能力Absence Management 缺勤管理Absence rate 缺勤率Absent with leave 因故缺勤(被)许可缺勤Absent without Leave 无故缺勤擅离职守Absenteeism 缺勤Accelerating Premium 累进奖金制Accident Frequency 事故频率Accident Insurance 意外伤害保险Accident Investigation 事故调查Accident Loss 事故损失Accident Prevention 事故预防Accident Proneness 事故(频发)倾向Accident Severity 事故严重程度Accident Severity Rate 事故严重率Accident Work Injury 工伤事故Achievement Need 成就需求Achievement Test 成就测试Action Learning 行动(为)学习法Action Research 行动研究Active Practice 自动实习Adjourning 解散期解散阶段Administer 管理者Administrative Level 管理层次Administrative Line 直线式管理ADR-Alternative Dispute Resolution 建设性争议解决方法Adventure learning 探险学习法Adverse Impact 负面影响Advertisement Recruiting 广告招聘Affective Commitment 情感认同Affiliation Need 归属需求Affirmative Action 反优先雇佣行动Age Composition 年龄结构Age Discrimination 年龄歧视Age Retirement 因龄退休Agreement Content 协议内容ALIEDIM 费茨帕特里克出勤管理模型Allowance 津贴Alternative Ranking Method 交替排序法Amoeba Management 变形虫式管理Analytic Approach 分析法Annual Bonus 年终分红Annual Leave 年假Annuity/Pension 退休金Applicant-Initiated Recruitment 自荐式招聘Application Blank 申请表Appraisal Feedback 考评反馈Appraisal Interview 考评面谈Appraisal Standardization 考评标准化Appraiser Training 考评者培训Apprenticeship Training 学徒式培训Arbitration/Mediation 仲裁Assessment Center 评价中心ATS-Applicant Tracking System 求职跟踪系统Attendance 考勤Attendance Incentive Plan 参与式激励计划Attendance Rate 出勤率Attitude Survey 态度调查Attribution Theory 归因理论Audiovisual Instruction 视听教学Authority 职权Availability Analysis 可获性分析Availability Forecast 供给预测Background Investigation 背景调查Balance-Sheet Approach 决算表平衡法Bargaining Issue 谈判问题BARS-Behaviorally Anchored Rating Scale Method 行为锚定等级法Basic Skill 基础技能Behavior Modeling 行为模拟Behavior Modification 行为矫正疗法Behavioral Description Interview 工作方式介绍面试Behavioral Rating 工作方式考核法BEI-behavior event interview 行为事件访谈法Benchmark Job 基准职位Benchmarking Management 标杆管理Benefit Plan 福利计划Benefit/Welfare 福利BFOQ-Bona Fide Occupational Qualification 实际职业资格Biological Approach 生物型工作设计法Board Interview 会议型面试BOS-Behavior Observation Scale 行为观察量表Borter-Lawler's theory of Expectency 波特—劳勒期望激励理论Bottom-Line Concept 底线概念Boundaryless Organizational Structure 无疆界组织结构Bounded Rationality 有限理性Brainstorm Ideas 头脑风暴法Broadbanding Pay Structure 扁平薪资结构BSC-balanced scorecard 平衡计分卡Burnout 精力耗尽Business Necessity 经营上的必要性Cafeteria-Style Benefit 自助式福利CAI-Computer-assisted Instruction 电脑辅助指导Campus Recruiting 校园招聘Candidate-Order Error 侯选人次序错误Career Anchors 职业锚/职业动机Career Counseling 职业咨询Career Curve 职业曲线Career Cycle 职业周期Career Development Method 职业发展方法Career Path 职业途径Career Path Information 职业途径信息Career Planning 职业规划career plateau 职业高原Career Stage 职业阶段Career Training 专业训练职业训练Career-Long Employment 终身雇佣制Case Studay Training Method 案例研究培训法CBT-Computer Based Training 以计算机为载体的培训Central Tendency 居中趋势CIPP-Context,Input,Process,Product CIPP 评估模型CIRO-Context Evaluation,Input Valuation,Reaction Evaluation,Output Evaluation CIRO 培训评估模式CIT-Critical Incident Technique 关键事件技术Classification Method 分类法Classroom Training 课堂培训Closed Shop 闭门企业CMI-Computer-managed Instruction 电脑管理指导Coaching 辅导教练Co-Determination 共同决策制Coercive Power 强制权力Cognitive Aptitude Test 认知能力测试Cohesiveness 凝聚力Colleague Appraisal 同事考评Collective Bargaining 劳资谈判Comparable Worth 可比价值Comparative Appraisal Method 比较评估法Compensable Factor 报酬要素Compensation & Benefit 薪酬福利Compensation Committee 报酬委员会Compensatory Time Off 补假Competence-Based Interview 基于能力的面试Competency Assessment 能力评估Competency 胜任特征Competency Model 胜任特征模型Competency-Based Education and Training 能力本位教育与训练Competency-Based Pay/Skill-Based Pay 技能工资Complex 情结Compressed Workweek 压缩工作周Compulsory Binding Arbitration 强制性仲裁Computerized Career Progression System 电脑化职业生涯行进系统Computerized Forecast 电脑化预测Conceptual Skill 概念性技能Conciliation 调解Concurrent Validity 同期正当性Conference Method 会议方法Conflict 冲突Conflict Management 冲突管理Construct Validity 结构效度Constructive Discharge 事实上的解雇Content Validity 内容效度Contractual Right 契约性权利Contrast Error 比较性错误Contributory Plan 须付费的退休金计划Coordination Training 合作培训Copayment 共同付费Core Competency 核心竞争力Core Value 核心价值观Core Worker 核心员工Core Workforce 核心工作团队Corporate Culture 企业文化Corporate Identity 企业识别Corporate Image 企业形象Correlation Analysis 相关分析Cost Per Hire 单位招聘成本Criterion-Related Validity 标准关联效度Critical Job Dimension 关键性工作因子Cross-Functional Training 跨功能训练Cross-Training 岗位轮换培训Culture Shock 文化冲突Cumulative Trauma Disorder 累积性工伤Cutoff Score 录用分数线Cyclical Variation 循环变动Decertification 取消认可Defined Benefit Plan 固定收益制Delphi Analysis 德尔菲分析Deutero Learning 再学习Differential Piece Rate 差额计件工资Dimission 离职Dimission Interview 离职面谈Dimission Rate 离职率Disciplinary Action 纪律处分Discriminant Analysis 判别分析dismissal reason 解雇理由disparate impact 差别性影响disparate treatment 差别性对待distribute bonus/profit sharing 分红distributive bargaining 分配式谈判distributive justice 分配公正diversity management 多样性管理diversity training 多样化培训division structure 事业部结构Double-Loop Learning 双环学习Downsizing 裁员DTL-Decision Tree Induction 决策树归纳法Dual Career Path 双重职业途径dust hazard 粉尘危害EAP-Employee Assistance Program 员工帮助计划Early Retirement 提前退休Early Retirement Factor 提前退休因素Early Retirement Window 提前退休窗口Earnings 薪资Economic Strike 经济罢工Education 学历Education Subsidy 教育津贴EEO-Equal Employment Opportunity 公平就业机会EEOC-Equal Employment Opportunity Commission 公平就业机会委员会Effect Factors of Career Planning 职业规划影响因素Effect Factors of Development 开发影响因素Effective Coaching Technique 有效的训练方法Effective Working Hour 有效工时Efficiency of Labor 劳动效率Efficiency Wage 效率工资Ego-Involvement 自我投入E-Learning 网络化学习Election Campaign 选举活动Electronic Meeting 电子会议Emotional Appeal 感召力Employee Attitude Surveys 员工态度调查Employee Career Management 员工职业生涯管理Employee Consultation Services 员工咨询服务Employee Equity 员工公平Employee Leasing 员工租借Employee Involvement 员工参与Employee Manual 员工手册Employee Orientation 员工向导Employee Ownership 员工所有制Employee Polygraph Protection Act 《雇员测谎保护法案》[美] Employee Potential 员工潜能Employee Referral 在职员工推荐Employee Retirement Income Security Act 《职工退休收入保障法》[美] Employee Safety and Health 员工安全和健康Employee Security 员工安全Employee Security Measures 员工安全措施Employee Self-Service 员工自助服务Employee Services Benefits 员工服务福利Employee Skill 员工技能Employee Stock Ownership Trust 企业员工持股信托Employee Surplus 员工过剩Employee Survey 员工测评Employee Training Method 员工培训方法Employee Turnover 员工流动Employee Turnover Rate 员工流动率Employee Under Training 受训员工Employee-Centered Job Redesign 以员工为中心的工作再设计Employees Bonus 雇员红利Employer Unfair Labor Practices 雇主不当劳动行为Employment 雇用Employment Agency 职业介绍所Employment Application Form 应聘申请表Employment at will 自由就业Employment Consultant 招聘顾问Employment Contract Renewal 雇用合同续签Employment Diseases 职业病Employment History 工作经历Employment Objective 应聘职位Employment Offer/Enrollment 录用Employment Relationship 员工关系Employment Separation Certificate 离职证明书Empowerment 激励自主Entitlement 授权法EQ-Emotional Quotient 情感智商EPA-Equal Pay Act 《平等工资法案》Equal Pay For Equal Work 同工同酬Equity Theory 公平理论E-Recruit 网络招聘ERG theory ERG 理论ERM-Employee Relationship Management 员工关系管理ERP-Enterprise Resource Planning 企业资源计划ESOP-Employee Stock Ownership Plan 员工持股计划Essay Method 叙述法ETS-Environmental Tobacco Smoke 工作场所吸烟问题E-Survey 电子调查Evaluation Criterion 评价标准Excellent Leader 优秀领导Executive Ability 执行力Executive Compensation 管理层薪资水平Executive Development Program 主管发展计划Executive Director 执行董事Executive Management 行政管理Executive Marketing Director 市场执行总监Executive Recruiters 高级猎头公司Executive Salaries 管理层工资Exempt Employee 豁免员工Exit Interview 离职面谈Expectancy Theory 期望理论Expectation 期望值Expected Salary 期望薪水Experimental Method 实验法Experimental Research 试验调查Expiry of Employment 雇用期满Exploit of HR 人力资源开发External Costs 外部成本External Employment 外部招聘External Environment of HR 人力资源外部环境External Equity 外部公平External Labor Supply 外部劳力供应External Recruiting Sources 外部招聘来源External Recruitment Environment 外部招聘环境Extra Work 加班Extrinsic Rewards 外部奖励Face Validity 表面效度Factor Comparison Method因素比较法Fair Labor Standards Act 《公平劳动标准法案》Family and Medical Leave Act 《家庭和医疗假期条例》[美] Fiedler Contingency Model 费德勒的权变模型First Impression Effect 初次印象效应Five-Day Workweek 每周五天工作制Fixed Term Appointment 固定期聘用Fixed Term Contract 固定任期合同Fixed Term Staff 固定期合同工FJA-Functional Job Analysis 功能性工作分析法Flat Organizational Structure 扁平化组织结构Flex Place 弹性工作地点Flex Plan 弹性工作计划flex time 弹性工作时间Flexible Benefits Program 弹性福利计划Forced Distribution Method 强制分配法Forced-Choice Method 强迫性选择法Formal Organization 正式组织Front-Line Manager 基层管理人员Full-Time 全职Function 职能Function of HRM 人力资源管理职能Functional Conflict Theory 冲突功能理论Functional Department 职能部门Funeral Leave 丧假Fundamental Attribution Error 基本归因误差Gain-Sharing Plan 收益分享计划Gang Boss 领班/小组长Gantt Charts 甘特图GATB-General Aptitude Test Battery 普通能力倾向成套测验General Union 总工会Given Role Playing 角色定位演示法Glass Ceiling 玻璃天花板Goal Conflict 目标冲突GOJA-Guidelines Oriented Job Analysis 指导性工作分析Golden Handshake 黄金握别Golden Parachute 黄金降落伞Graphic Rating Scale 图尺度评价法Grievance Mediation 抱怨调解Grievance Procedure 抱怨程序Gross Pay/Total Payroll 工资总额Group Appraisal 小组评价Group/Team Bonus 团体/小组奖金Group Congeniality/Cohesiveness 群体凝集力Group Life Insurance 团体人寿保险Group Pension Plan 团体退休金计划Group Piece Work 集体计件制Guaranteed Employment Offer 雇用信H·C·Gantt Premium System 甘特奖励工资制H·Emerson Premium System 艾末生奖励工资制Halo Effect 晕轮效应Halseys Premium System 哈尔赛奖励工资制Handwriting Analysis 笔迹分析法Headhunting 猎头Health Insurance 健康保险H-Form/Holding Company H 型结构Hierarchy of Needs Theory 需要层次理论High Performance Organization 高绩效组织High-Performance Work System 高绩效工作系统HMO-Health Maintenance Organization 健康维护组织Holiday Pay 假日薪水Home/Family Leave 探亲假Horizontal Career Path 横向职业途径Hot Stove Rule 热炉规则Housing/Rental Allowance 住房补贴HR Generalist 人力资源通才HR Information System 人力资源信息系统HR Manager 人力资源经理HR Officer 人力资源主任HR Policy 人力资源政策HRCI-Human Resource Certification Institute 人力资源认证机构HRD Appraisal 人力资源开发评价HRD Intermediary 人力资源开发媒介HRD Process 人力资源开发过程HRD-Human Resource Development 人力资源开发HRM-Human Resource Management 人力资源管理HRP-Human Resource Planning 人力资源规划Human Relations Movement 人际关系运动Hygiene Factor 保健因素Hypnosis 催眠Ill-Health Retirement 病退In-Basket Training 篮中训练Incentive Compensation/Reward Payment/Premium 奖金Incentive Plan 激励计划Incentive-Suggestion System 奖励建议制度Incident Process 事件处理法Independent Contractor 合同工Indirect Financial Compensation 间接经济报酬Individual Incentive Plan 个人奖金方案Individual Income Tax 个人所得税Individual Interview 个别谈话Individual Retirement Account 个人退休账户Industrial Injury Compensation 工伤补偿Industrial Union 产业工会Informal Communication 非正式沟通Informal Organization 非正式组织In-House Training 在公司内的培训Initial Interview 初试Insurance Benefit 保险福利Internal Environment of HR 人力资源内部环境Internal Equity 内部公平Internal Growth Strategy 内部成长战略Internal Job Posting 内部职位公开招聘Internal Recruitment 内部招聘Internal Recruitment Environment 内部招聘环境Interpersonal Skill 人际交往能力Interview Appraisal 面谈考评Interview Content 面试内容Interview Method 访谈法Interview Objective 面试目标Interview Planning List 面试计划表Intrinsic Reward 内在奖励Jack Welch's Management 韦尔奇式管理JAS-Job Analysis Schedule 工作分析计划表Job 工作、职业Job Account 工作统计Job Action 变相罢工(如怠工、放慢速度等) Job Aid 工作辅助Job Assignment 工作分配Job Analysis 工作分析Job Analysis Formula 工作分析公式Job Analysis Methods 工作分析方法Job Analysis Information 工作分析信息Job Analysis Process 工作分析流程JAP-Job Analysis Program 工作分析程序法Job Attitude 工作态度Job Bidding 竞争上岗Job Card 工作单Job Characteristic 工作因素Job Characteristics Model 工作特性模式Job Classification 职位分类Job Clinic 职业问题咨询所Job Code 工作编号,职位编号Job Context 工作背景Job Description 职位描述,工作说明Job Design 工作设计Job Enlargement 工作扩大化Job Enrichment 工作丰富化Job Evaluation 工作评估Job-Family 工作群Job Identification 工作识别Job Involvement 工作投入Job Inventory 工作测量表Job Knowledge Test 业务知识测试Job Morale 工作情绪Job Performance 工作表现Job Plan 工作计划Job Posting 公开招聘Job Pricing 工作定价Job Qualification and Restriction 工作任职条件和资格Job Redesign 工作再设计Job Rotation 工作轮换Job Satisfaction 工作满意度Job Security 工作安全感Job Scope 工作范围Job Sharing 临时性工作分担Job Specialization 工作专业化Job Specification 工作要求细则Job Standard 工作标准Job Stress 工作压力Job Surrounding 工作环境Job Time Card 工作时间卡Job Vacancy 职业空缺,岗位空缺Job-hop 跳槽频繁者Job-posting system 工作告示系统JTPA-Job Training Partnership Act 《职业培训协作法》J·S·Adams Equity Theory 亚当斯的公平理论Junior Board 初级董事会Johari Window 约哈瑞窗户Just Cause 正当理由Karoshi 过劳死Keogh Plan 基欧计划KPI-key Process Indication 企业关键业绩指标Kirkpatrick's Four-level Model of Evaluation 四阶层评估模型Knowledge Database 知识数据库Knowledge Management 知识管理KSA-knowledge ,skill, attitude 知识,技能,态度Labor Clause 劳工协议条款Labor Condition 劳动条件Labor Contract 劳动合同,雇佣合同Labor Contract Renewal 劳动合同续签Labor Cost 劳动成本Labor Demand Forecast 劳动力需求预测Labor Discipline 劳动纪律Labor Dispute 劳动纠纷Labor Exchange/Employment Agency 职业介绍所Labor Handbook 劳动手册Labor Insurance 劳保Labor Laws 劳动法Labor Management Relations Act 《劳动关系法》Labor Market 劳动力市场Labor Protection 劳动保护Labor Rate Variance 工资率差异Labor Redundance 劳动力过剩Labor Relation 劳动关系Labor Relation Consultant 劳工关系顾问Labor Relations Process 劳工关系进程Labor Reserve 劳动力储备Labor Shortage 劳动力短缺Labor Stability Index 人力稳定指数Labor Wastage Index 人力耗损指数Labor/Trade Union 工会Labor/Working Hour 人工工时Labor-Management 劳动管理Lateral Communication 横向沟通Lateral Thinking 横向思维Layoff 临时解雇Layoff Process 临时解雇程序Leader Attach Training 领导者匹配训练Leaderless Group Discussion 无领导小组讨论法Leader-Member Exchange Theory 领导者-成员交换理论Leader-Member Relation 上下级关系Leader-Participation Model 领导参与模式Leadership 领导能力Learning Curve 学习曲线Learning Organization 学习型组织Learning Performance Test 学习绩效测试Legitimate Power 合法权力Level-to-Level Administration 分级管理Life Cycle Theory of Leadership 领导生命周期理论Life Insurance 人寿保险Likes and Dislikes Survey 好恶调查表Limitation Factors of PA 考评的限制因素Line Manager 直线经理Line Authority 直线职权Line-Staff Relationship 直线参谋关系Line Structure 直线结构Loaned Personnel 借调人员Lockout 停工闭厂Locus of Control 内外控倾向Long Term Trend 长期趋势Long-Distance Education 远程教育Long-Range Strategy 长期策略Long-Term Contract 长期合同Lower Management 基层管理Lower-Order Need 低层次需求Lump Sum Bonus/Pay Incentive 绩效奖金Lump-Sum Merit Program 一次性总付绩效报酬计划Managed Care 有控制的医疗保健Management As Porpoise 海豚式管理Management Assessment Center 管理评价中心Management by Walking About 走动管理Management Development 管理层开发Management Development of IBM IBM 的管理层开发Management of Human Resource Development 人力资源开发管理Management Psychology 管理心理学Management Right 管理权Management Risk 管理风险Management Tool 管理工具Management Training 管理培训Managerial Art 管理艺术Managerial Authority 管理权威Managerial Function 管理职能Managerial Grid Theory 管理方格理论Mandated Benefit 强制性福利Mandatory Bargaining Issue 强制性谈判项目Marital Status 婚姻状况Market Price 市场工资Markov Analysis 马尔可夫分析过程Marriage Leave 婚假Massed Practice 集中练习集中学习Matrix Structure 矩阵结构MBO-Management By Objective 目标管理MBTI-Myers-Briggs Type Indicator 迈尔斯—布里格个性类型测量表Mc-Clelland's Theory of Needs 麦克里兰需要理论McDonnell-Douglas Test 麦当纳道格拉斯法Mechanistic Approach 机械型工作设计法Mediator/Negotiator 调解人Medical Insurance 医疗保险Medical/Physical Ability Inspection/Physical Ability Test 体检Membership Group 实属群体Mental Ability Test 逻辑思维测试Mentor 指导者Mentoring 辅导制Mentoring Function 指导功能Merit Pay 绩效工资Merit Raise 绩效加薪Metrics-Driven Staffing Model 标准驱动招聘模式Mid-Career Crisis Sub Stage 中期职业危机阶段Minimum Wage 最低工资Mission Installation Allowance 出差津贴Mixed-Standard Scale Method 多重标准尺度法Motivation 激励Motivational Approach 激励型工作设计法Motivational Factor 激励因素Motivational Pattern 激励方式Motivation-hygiene Theory 激励保健论MPS-Motivating Potential Score 激励潜能分数Multidivisional Structure M 型结构Multimedia Technology 多媒体技术Multiple Cutoff Model 多切点模式Multiple Hurdle Model 跨栏模式National Culture 民族文化National Union (国家)总工会Needs Assessment 需求评估Negligent Hiring 随意雇佣Nepotism 裙带关系Network Career Path 网状职业途径Networking 网络化(组织)NGT-Nominal Group Technique 群体决策法No Financial Compensation 非经济报酬Noncontributory Plan 非付费退休金计划Nondirective Interview 非定向面试Nondiscrimination Rule 非歧视性原则Nonexempt Employee 非豁免的员工Nonverbal Communication 非言语沟通No-Pay Study Leave 无薪进修假期Normal Retirement 正常退休Normative Analysis 规范分析法No-Smoking Rule 禁烟规定object teaching 实物教学,直观教学observation method 观察法occupational choice 职业选择occupational disease 职业病occupational environment 职业环境occupational guidance 职业指导,就业指导Occupational Health &Safety Training 职业安全与卫生培训occupational market condition 职业市场状况occupational mobility 职业流动性occupational outlook handbook 职业展望手册offer letter 录用通知书off-the-job training 脱产培训Ombudsperson 督察专员OMS-Occupational Measurement System 职业测定系统on boarding training 入职培训on-the-job training 在职培训open-door policy 门户开放政策opinion survey 意见调查organization 组织organization change and development 组织变革与发展organization character 组织特征organization design 组织设计organization development appraisal 组织发展评价organization development method 组织发展方法organization environment 组织环境organization goal 组织目标organization renewal 组织革新organization size 组织规模organization structure 组织结构organizational analysis 组织分析organizational authority 组织职权organizational career planning 组织职业规划organizational citizenship behavior 组织公民行为organizational climate 组织气候organizational commitment 组织认同感organizational diagnosis 组织诊断organizational function 组织职能organizational level 组织层次organizational merger 组织合并organizational orientation 组织定位organizational/job stress 组织/工作压力organization-centered career planning 以企业为中心的职业计划organized administration 组织管理orientation 岗前培训orientation objective 岗前培训目标orientation period 岗前培训阶段OSHA standard 美国职业安全与健康局/职业安全与健康法案标准out placement 岗外安置oversea assignment 海外工作overtime hour 加班工时overtime wage 加班工资overtime work 加班paired comparison method 配对比较法panel/group interview 小组面试PA-Performance Analysis 绩效分析Parkinson's Law 帕金森定律participant diary 现场工人日记participative management 参与式管理part-time job 兼职PAS-Performance Appraisal 绩效评估体系pattern bargaining 模式谈判patterned behavior description interview 模式化行为描述面试pay calculation 工资结算pay card 工资卡pay cheque/employee paycheck 工资支票pay compression 压缩工资Pay day 发薪日pay equity 报酬公平pay freeze 工资冻结pay grade 工资等级pay period 工资结算周期pay range 工资幅度pay rate 工资率pay rate adjustment 工资率调整pay secrecy 工资保密pay slip/envelop 工资单pay survey 薪酬调查pay/salary rate standard 工资率标准payroll system 工资管理系统Payroll tax 工资所得税payroll/wage analysis 工资分析payroll/wage form 工资形式payroll/wage fund 工资基金pension plan 退休金计划pension/retirement benefit 退休福利people-first value " 以人为本"的价值观perceptual-motor approach 知觉运动型工作设计法performance appraisal 绩效评估performance appraisal interview 绩效评估面谈performance appraisal objective 绩效评估目标performance appraisal period 考评期performance appraisal principle 绩效评估原则performance feedback 绩效反馈performance management system 绩效管理制度performance standard 绩效标准performance-reward relationship 绩效与报酬关系periodic salary adjustment 定期薪资调整permissive management 放任式管理personal character 个人性格,个性personal grievance 个人抱怨personal information record 人事档案personal leave 事假personality test 个性测试Personality-Job Fit Theory 性格与工作搭配理论personnel selection 选拔personnel test 人格测验品格测验Peter M. Senge's Theory of Learning Organization 彼德·圣吉的学习型组织理论physiological need 生理需要piece-rate system 计件工资制pink slip 解雇通知point method 因素计点法polygraph test 测谎测试position analysis questionnaire 职位分析问卷法position description 职位描述position vacant 招聘职位positional level 职位层次positional title 职称post wage system 岗位工资制power distance 权力距离practice 实习predictive validity 预测效度premium plan/incentive system/reward system 奖金制pre-natal/maternity leave 产假prescribed group 正式群体primary welfare 基本福利privacy right 隐私权prize contest 奖励竞争probationary term/probation period 试用期problem-solving team 问题解决团队procedural justice 过程正义process benchmarking 流程标杆管理professional certificate 职业资格证书professional competence/capacity 专业能力professional ethics 职业道德professional examination 专业考试professional liability insurance 职业责任保险professional manager 职业经理人profit-sharing plan 利润分享计划programmed instruction 程序教学projective personality test 人格投射测试promote/demote 晋升/降职protected group 受保护群体psychic reward 精神奖励psychoanalysis 心理分析psychological characteristic/feature 心理特征psychological contract 心理/精神契约psychological factor 心理因素psychological goal 心理目标psychological phenomenon 心理现象psychological test/psychometry 心理测验心理测试psychomotor abilities test 运动神经能力测试quality circles 质量圈quantity of applicant 侯选人数量questionnaire method 问卷调查法quit rate 离职率Race Discrimination 种族歧视Ranking Method 排序法Rater Bias 评估偏差Rating Certificate 等级证书Ratio Analysis 比率分析法Realistic Job Preview 实际岗位演习Reality Shock 现实冲击Reallocate 重新安排重新分配Recommend 员工推荐Recreation Leave Allowance 休假津贴Recreation/Sabbatical Leave 休假Recruiter 招聘人员Recruitment 招聘Recruitment Ditch 招聘渠道Recruitment Examination 招聘考试Recruitment Method 招聘方法Recruitment Optional Program 招聘备择方案Recruitment Task Guide 招募工作指导Red-Circled Employee 红圈员工Reducing Accident 减少事故Reducing Burnout 减少衰竭Reengineering the Corporation 企业再造Reference Check 个人证明材料检查Refusing Applicant 拒绝求职者Regency Effect 近因性错误Regression Analysis 回归分析Regular Earning/Pay/Wage 固定工资Regular Incentive 常规奖励Rehiring 回聘Reinforcement Theory 强化理论Reliability Evaluation 信度评估Renege 违约Replacement Cost 重置成本Requirement Identification 需求识别Requisite Task Attributes Theory 必要任务属性理论Resignation 辞职Resume 简历Resume Inventory 简历数据库Resumption from Leave 销假Retiree System 退休制度Retirement 退休Retirement Age 退休年龄Retirement Fund 退休基金Return of Talent 人才回流Rewarding by Merit/Pay According to Work 业绩报酬Right to Rest and Leisure 休息权Risk Pay Planning 风险工资计划Rokeach Values Survey 罗克奇价值观调查表Role Ambiguity 角色模糊Role Behavior 角色行为Role Conflict 角色冲突Role Playing 角色扮演Roles of HRM 人力资源管理角色Roll-Down Training 自上而下分级培训法Safety Director 安全负责人Safety Inspection 安全检验Safety Measure 安全措施Safety Program 安全方案Safety Training 安全培训Salary Administration 薪水管理Salary Band/Range 薪水范围Salary Survey 薪资调查Satisficing Decision Model 满意决策模型Scanlon Plan 斯坎伦计划Scatter Plot 散点分析Selection 选拔Selection Criteria 选拔准则Selection Decision 选拔决策Self-Actualization Need 自我实现需要Self-Assessment 自我评价Self-Assessment Tool 自我评估工具Self-Efficacy 自我效能Self-Managed Work Team 自我管理工作团队Self-Perception Theory 自我知觉理论Self-Serving Bias 自我服务偏差Seniority 资历Sensitivity Training 人际敏感性训练Serialized /Sequential Interview 系列式面试Severance Pay 告别费Sexual Discrimination 性别歧视Sexual Harassment 性骚扰Shift Differential 值班津贴Short-Term Contract 短期合同Silver Handshake 银色握手Simulation Exercise 模拟练习Single-Loop Learning 单环学习Situational Interview 情景面试Situational Leadership Theory 情境领导理论Skill Inventory 技能量表Skip-Level Interview 越级谈话SMART SMART 分析法Social Security 社会保障Special Purpose Team 特殊目的团队Special Training 特别训练Specialized Course 专门课程Spot Bonus 即时奖金Stabilization Sub Stage 稳定阶段Staff Authority 参谋职权Standard Labor Cost 标准人工成本Standard Wage Rate 标准工资率Statutory Holidays 法定假期Statutory Right 法定权利Stock Option 持股权Straight Piece-Rate System 直接计件工资制Strategic HRD 战略性人力资源开发Strategic HRM 战略性人力资源管理Strength/Weakness Balance Sheet 强/弱平衡表Stress 压力Stress Interview 压力面试Stress Source 压力来源Strictness/Leniency Tendency 偏松或偏紧倾向Strike 罢工Structure Employment 结构性就业Structured Interview 结构化面试Subculture 亚文化Subordinate Appraisal 下级考评Succession Planning System 接班人规划系统Suggestion System 建议制度Superordinate Appraisal 上级考评Supplement Pay 补充报酬Supplemental Unemployment Benefit 补充性失业福利Survey Feedback 调查反馈Survival Rate 留任率SWOT SWOT 分析法Sympathy Strike 同情罢工Synectics 综摄法分合法System Structure 系统结构Systematic Training Model 分类训练模式Systemic Thinking 系统性思考Talent 人才TA-Transactional Analysis 人际关系心理分析(交互作用分析)TAT-Thematic Apperception Test 主题统觉测试Tax Equalization Plan 税负平衡计划Teaching 讲授法Team Building 团队建设Team Spirit 协作精神Team/Group Incentive Plan 团队激励计划Telecommuting Job 远距离工作Termination at Will 随意解雇Test Reliability 测试信度Test Validity 测试效度The Allport-Vernon-Lindzey Study of Values 奥波特-凡农-林德赛的价值观研究The Trade Union Law of the People's Republic of China 《中华人民共和国工会法》Theory X X 理论Theory Y Y 理论Time Management 时间管理Timework Work 计时工作TM-Transcendental Meditation 超自然冥想Traditional Career Path 传统职业途径Trainer 培训师Training 培训Training &Development Manager 培训经理Training Administration 培训管理Training Design 培训设计Training Function 培训职能Training Item 培训项目Training Needs Analysis 培训需求分析Training Outcome 培训结果Training Plan 培训计划Training Specialist 培训专员Transfer 调动Travel Allowance 旅行津贴Traveling Expenses Standard 差旅费标准Treatment 待遇Trend Analysis 趋势分析Turnover 人事变动Unclear PA Standard 不明确的绩效评估标准Undue Hardship 过度重负Unemployment 失业Unemployment Compensation 失业津贴Unemployment Insurance 失业保险Unemployment Rate 失业率Union Authorization Card 工会授权卡Union Steward/Delegate 工会代表Union-Free Policy 无工会政策Unit Labor Cost 单位劳动成本Unitary Structure U 型结构(一元结构)Unregistered Employment 隐性就业Unsafe act 不安全行为Unsafe Condition 不安全条件Unstructured Interview 非结构化面试Vacation 假期Value-Based Hiring 价值观为基础的雇佣Variable Compensation 可变报酬Vestibule Training 新员工培训技工学校培训Vesting 既定享受退休金权利Violence in the Workplace 工作场所暴力Virtual Organization 虚拟组织Virtual Team 虚拟团队Voluntary Pay Cut 自愿减少工资方案Voluntary Protection Program 自愿保护项目VPT-Vocational Preference Test 职业性向测试Wage Accounting 工资核算Wage Audit 工资审计Wage by Seniority System/Wage-by-Age System 工龄工资制Wage Control 工资控制Wage Curve 工资曲线Wage Deduction 工资扣除额Wage in Cash 现金工资Wage in Kind 实物工资Wage in Sliding Scale 浮动工资Wage Index 工资指数Wage Level 工资水平Wage Plan 工资计划Wage Policy 工资政策Wage Rate Per Hour 计时工资Wage Standard 工资标准Wage Structure 工资结构Wage System 工资制度Wage-Incentive Plan 奖励工资制Warren G.Bennis's Theory of Group development 沃伦·本尼斯的组织发展理论WBS-Work Breakdown Structure 工作分解结构Web Based Training 网络培训Welfare Management 福利管理Welfare Staff 福利工作人员Wellness Program 平安计划Well-Pay 平安费William Ouchi Theory Z 威廉.大内的Z 理论Work & Life Balance 工作生活平衡Work Age 工龄Work Attitude 工作态度Work Behavior 工作行为Work Demand 工作要求Work Efficiency 工作效率Work Out 合力促进Work Pressure 工作压力Work Sample 工作样本Work Sampling Technique 工作样本技术Work Schedule 工作进度表Worker Involvement 雇员参与Workplace Learning 工作场所学习Work-Related Injury Leave 工伤假Work-Sample Test 工作样本测试Written Examination 笔试Wrongful Discharge 不当解雇Xerox Program 施乐方案Yellow-Dog Contract 黄狗合同Zero-Base Forecast 零基预测A1.Acceptability可接受性2.Achievement tests成就测试3.Action plan 行动计划4.Action steps 行动步骤5.Adventure learning 探险学习法6.Adverse impact 负面影响7.Alternative dispute resolution(ADR) 建设性争议解决方法8.Analytic approach 分析法9.Appraisal politics 评价政治学10.apprenticeship 学徒制11.Arbitrary 仲裁12.Assessment 评价13.Assessment center 评价中心C22.Career 职业23.Career counseling 职业咨询24.Career curves (maturity curves)职业曲线(成熟曲线)25.Career management system职业管理系统26.Career support 职业支持27.Centralization 集权化munity of practice 演练小组pa-ratio 比较比率pensable factors 报酬要素petency assessment 能力评估petitive advantage 竞争优势33.Concentration strategy 集中战略34.Concurrent validation 同时效度35.Consumer price index,CPI 消费者价格指数36.Core competencies 核心竞争力37.Criterion-related validity效标关联效度38.Critical incident 关键事件39.Critical incident method关键事件法40.Cross-cultural preparation跨文化准备B14.Basic skills 基本技能15.Behavior-based program行为改变计划16.Behavior modeling 行为模拟17.Benchmarks 标杆18.Benchmarking 评判19.Benefits 收益20.Bonus 奖金21.Boycott 联合抵制D45.Data flow diagram 数据流程图46.Database 数据库47.Decentralization 分散化48.Delayering 扁平化49.Depression 沮丧50.Development planning system开发规划系统51.Differential piece rate差额计件工资52.Direct costs 直接成本53.Discipline 纪律54.Disparate impact 差别性影响55.Disparate treatment 差别性对待56.Diversity training 多元化培训57.Downsizing 精简58.Downward move 降级41.Cross-training 交叉培训42.Cultural environment 文化环境43.Cultural shock 文化冲击44.Customer appraisal 顾客评估E59.Efficiency wage theory效率工资理论60.Electronic performance support system(EPSS)电子绩效支持系统61.Employee empowerment 员工授权62.Employee leasing 员工租借63.Ethics 道德64.Expatriate 外派雇员65.Expert systems 专家系统66.External analysis 外部分析67.External growth strategy外部成长战略68.External labor market 外部劳动力市场G75.Gain sharing plans 收益分享计划76.Globalization 全球化77.Goals 目标78.Goals and timetables 目标和时间表79.Graphic rating-scale method图示评估法80.Group-building methods团队建设法81.Group mentoring program群体指导计划I90.Indirect costs 间接成本91.Individualism/collectivism个人主义/集体主义92.Input 投入93.Instructional design process指导性设计过程94.Internal analysis 内部分析95.Internal growth strategy内部成长战略96.Internship programs 实习计划97.Interview 面试98.Intraorganizational bargaining组织内谈判K115.Key jobs 关键工作Lbor market 劳动力市场bor relations process劳动关系进程118.Leaderless group discussion无领导小组讨论法119.Learning organization学习型组织120.Long-term-short-team orientation长期-短期导向M121.Maintenance of membership会员资格维持122.Management by objectives,MBO目标管理123.Management forecasts 管理预测124.Management prerogatives 管理特权125.Manager and/or supervisor appraisal经理和/或上司评估126.Managing diversity 管理多元化127.Markov analysis 马克夫分析法128.Mediation 调解F69.Factor comparison system因素比较法70.Feedback 反馈71.Forecasting(劳动力供求)预测72.Formal education programs正规教育计划73.Frame of reference 参照系74.Functional job analysis,FJA职能工作分析H82.Hay profile method 海氏剖析法83.High-leverage training高层次培训84.High-performance work systems高绩效工作系统85.Hourly work 计时工资制86.Human capital 人力资本87.Human resource information system(HRIS)人力资源信息系统88.Human resource management人力资源管理89.Human resources planning,HRP人力资源计划J99.Job analysis 工作分析100.Job classification system工作分类法101.Job description 工作描述102.Job design 工作设计103.Job enlargement 工作扩大化104.Job enrichment 工作丰富化105.Job evaluation 工作评价106.Job experiences 工作经验107.Job involvement 工作认同108.Job posting and bidding工作张贴和申请109.Job progressions 工作提升110.Job ranking system工作重要性排序法111.Job rotation 工作轮换112.Job satisfaction 工作满意度113.Job specification 工作规范114.Job structure 工作结构。
美国国家教师教育技术标准目前,我国在教师教育技术标准方面的研究和实践还比较贫乏,尽管各类教师信息技术培训、信息技术与课程整合的培训非常多,但是这些培训尚没有统一的标准可以参照。
教师究竟应该具备哪些有关信息技术的基本知识和技能,具备哪些运用信息技术进行教学的知识和技能,才能有效地在课堂教学中使用信息技术?美国早在1993年就制定了国家教师教育技术标准(第一版),并将其作为审核教师认证、培训相关项目的依据。
美国国家教师教育技术标准无疑对我国有很大的借鉴价值。
1993年,国际教育技术联合会(International Society for Technology in Education,简称ISTE)制定了美国国家教师教育技术标准(National Edu-cational Technology Standard for Teachers,简称NETS,第一版)。
教师教育技术标准说明了教师在教学中有效运用计算机和其他电子设备所必须具备的技能和知识。
美国国家教师教育认证委员会(T h eNational Council for Accreditation of Teacher Education,简称NCATE)将这个标准作为审核教师认证、培训相关项目的依据。
一、简介ISTE制定的NETS在美国全国范围的大学、各州教育部门和学区得到了广泛的使用,成为技术在教学中应用的主要指导框架。
这个标准经历了3次修改和发展:1.1993年,第一版,针对所有教师的技术标准,有13个行为指导。
2.1997年,第二版,针对所有教师的技术标准,有18个行为指导,分别属于3个能力范畴:●基本的计算机/技术操作和概念●技术在教师个人的生活和教学工作中的使用●技术在教学中的应用3.2000年,第三版,与ISTE制定的国家学生技术标准一致,并体现了有关使用技术进行教和学的研究,以及技术方面的进步。
第三版将3个能力范畴扩展为6个:将技术在教学中的应用分解为计划、应用和评价,并增加了与技术使用有关的社会、道德、法律和人性问题:●技术的操作和概念●策划、设计学习环境和过程●教学、学习与课程●测试与评估●工作实效和职业实践●社会、道德、法律和人性方面的问题第三版包括23个行为指导。
pattern classification英文版Pattern ClassificationPattern classification is a branch of machine learning that focuses on classifying data or objects based on their features or characteristics. It involves the use of algorithms and statistical techniques to analyze and categorize patterns in data.The process of pattern classification involves several steps, including data preprocessing, feature extraction, model training, and model evaluation. These steps aim to transform raw data into a format that can be easily analyzed and used for classification.In data preprocessing, the raw data is cleaned and normalized to remove any inconsistencies or errors. This ensures that the data is reliable and can be effectively used for classification.Feature extraction is the process of selecting relevant features from the data. This involves identifying the most discriminative features that can best distinguish between different classes. Feature extraction techniques can include statistical measures, dimensionality reduction, or transformations.Once the features have been extracted, a classification model is trained using a labeled dataset. Various algorithms can be used for training, such as decision trees, support vector machines, or neural networks. The model learns from the labeled data and establishes patterns to make predictions on unseen data.To evaluate the performance of the classification model, it is testedon a separate dataset called the test set. Different performance metrics such as accuracy, precision, recall, and F1 score are calculated to assess the model's effectiveness.Pattern classification has various applications in fields such as computer vision, speech recognition, bioinformatics, and data mining. It is used to solve problems such as image recognition, document classification, fault detection, and sentiment analysis.In summary, pattern classification is the process of categorizing data based on its features. It involves data preprocessing, feature extraction, model training, and model evaluation. This field plays a crucial role in various real-world applications and contributes to the advancement of machine learning and artificial intelligence.。
classificationClassification is a fundamental task in machine learning and data analysis. It involves categorizing data into predefined classes or categories based on their features or characteristics. The goal of classification is to build a model that can accurately predict the class of new, unseen instances.In this document, we will explore the concept of classification, different types of classification algorithms, and their applications in various domains. We will also discuss the process of building and evaluating a classification model.I. Introduction to ClassificationA. Definition and Importance of ClassificationClassification is the process of assigning predefined labels or classes to instances based on their relevant features. It plays a vital role in numerous fields, including finance, healthcare, marketing, and customer service. By classifying data, organizations can make informed decisions, automate processes, and enhance efficiency.B. Types of Classification Problems1. Binary Classification: In binary classification, instances are classified into one of two classes. For example, spam detection, fraud detection, and sentiment analysis are binary classification problems.2. Multi-class Classification: In multi-class classification, instances are classified into more than two classes. Examples of multi-class classification problems include document categorization, image recognition, and disease diagnosis.II. Classification AlgorithmsA. Decision TreesDecision trees are widely used for classification tasks. They provide a clear and interpretable way to classify instances by creating a tree-like model. Decision trees use a set of rules based on features to make decisions, leading down different branches until a leaf node (class label) is reached. Some popular decision tree algorithms include C4.5, CART, and Random Forest.B. Naive BayesNaive Bayes is a probabilistic classification algorithm based on Bayes' theorem. It assumes that the features are statistically independent of each other, despite the simplifying assumption, which often doesn't hold in the realworld. Naive Bayes is known for its simplicity and efficiency and works well in text classification and spam filtering.C. Support Vector MachinesSupport Vector Machines (SVMs) are powerful classification algorithms that find the optimal hyperplane in high-dimensional space to separate instances into different classes. SVMs are good at dealing with linear and non-linear classification problems. They have applications in image recognition, hand-written digit recognition, and text categorization.D. K-Nearest Neighbors (KNN)K-Nearest Neighbors is a simple yet effective classification algorithm. It classifies an instance based on its k nearest neighbors in the training set. KNN is a non-parametric algorithm, meaning it does not assume any specific distribution of the data. It has applications in recommendation systems and pattern recognition.E. Artificial Neural Networks (ANN)Artificial Neural Networks are inspired by the biological structure of the human brain. They consist of interconnected nodes (neurons) organized in layers. ANN algorithms, such asMultilayer Perceptron and Convolutional Neural Networks, have achieved remarkable success in various classification tasks, including image recognition, speech recognition, and natural language processing.III. Building a Classification ModelA. Data PreprocessingBefore implementing a classification algorithm, data preprocessing is necessary. This step involves cleaning the data, handling missing values, and encoding categorical variables. It may also include feature scaling and dimensionality reduction techniques like Principal Component Analysis (PCA).B. Training and TestingTo build a classification model, a labeled dataset is divided into a training set and a testing set. The training set is used to fit the model on the data, while the testing set is used to evaluate the performance of the model. Cross-validation techniques like k-fold cross-validation can be used to obtain more accurate estimates of the model's performance.C. Evaluation MetricsSeveral metrics can be used to evaluate the performance of a classification model. Accuracy, precision, recall, and F1-score are commonly used metrics. Additionally, ROC curves and AUC (Area Under Curve) can assess the model's performance across different probability thresholds.IV. Applications of ClassificationA. Spam DetectionClassification algorithms can be used to detect spam emails accurately. By training a model on a dataset of labeled spam and non-spam emails, it can learn to classify incoming emails as either spam or legitimate.B. Fraud DetectionClassification algorithms are essential in fraud detection systems. By analyzing features such as account activity, transaction patterns, and user behavior, a model can identify potentially fraudulent transactions or activities.C. Disease DiagnosisClassification algorithms can assist in disease diagnosis by analyzing patient data, including symptoms, medical history, and test results. By comparing the patient's data againsthistorical data, the model can predict the likelihood of a specific disease.D. Image RecognitionClassification algorithms, particularly deep learning algorithms like Convolutional Neural Networks (CNNs), have revolutionized image recognition tasks. They can accurately identify objects or scenes in images, enabling applications like facial recognition and autonomous driving.V. ConclusionClassification is a vital task in machine learning and data analysis. It enables us to categorize instances into different classes based on their features. By understanding different classification algorithms and their applications, organizations can make better decisions, automate processes, and gain valuable insights from their data.。
UL认证介绍:英文保险商试验所(Underwriter Laboratories Inc.简称UL)是美国最有权威的,也是界上从事安全试验和鉴定的较大的民间机构。
它是一个独立的、非营利的、为公共安全做试验的专业机构。
其业务包括:有关材料、工具、产品、设备、构造、方法和系统筹对是否危及人的生命财产的安全进行实验。
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UL认证流程产品申请UL标志包括以下几个步骤:1.申请人递交有关公司及产品资料书面申请:您应以书面方式要求UL公司对贵公司的产品进行检测。
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CNAS国际认可论证IAF是国际认可论坛IAF是国际认可论坛(International Accreditation Forum)的缩写,它是由有关国家认可机构参加的多边合作组织,成立于1993年1月,现有成员30多个,中国合格评定国家认可委员会(CNAS)是其成员单位之一,中国也是17个发起国之一。
其主要目标是协调各国认证制度,通过统一规范各成员国的审核员资格要求、培训准则及质量体系认证机构的评定和认证程序,使其在技术运作上保持一致,从而确保有效的国际互认,它在世界上包括两大组织,分别是欧洲认证认可组织(EAC)和太平洋认可合作组织(PAC)。
以认可项目等效性为基础,国际认可论坛多边承认协议签约的认可机构批准的认可,使组织持有在世界的某一地区已被认可的认证证书能在世界的任何地区被承认。
因此,被IAF多边承认协议签约认可机构认可的认证机构在管理体系、产品、服务、人员和其它类似的符合性评审项目所颁发的认证证书在国际贸易等领域均能得到世界各国承认与信任。
欧洲认证认可组织EAC欧洲认证认可组织EAC 始建于1991年,目的是在欧洲建立一个区域性的认可制度,实现对各成员国的认证机构能力的相互承认,从而达到对认证证书的相互承认。
EAC 的组成成员主要来自欧洲经济共同体和欧洲自由贸易联盟成员国的国家认可机构。
在各通过同行评定的加盟成员国认可机构间签署多边承认协议。
同行评定是指由各认可机构派代表组成联合审核组,依据ISO/CAS_CO226、ISO/CA8CO227及EN45012和 ISO/IEC48号指南对其他认可机构进行能力评审。
已签署协议的有:FINAS芬兰、RVC荷兰、NA挪威、SWEDAC瑞典、SAS瑞士、NACCB英国。
太平洋认可合作组织太平洋认可合作组织(Pacific Accreditation Cooperation, 英文缩写PAC),是由亚太经济合作组织(APEC)成员经济体的认证机构的认可机构或类似合格评定机构的认可机构及利益相关方组成的协会。
猎头顾问常用英语词汇大全16PF卡特尔16种人格因素测试360-degreeappraisal360度评估360-degreefeedback360度反馈7S7S原则/模型New7S新7S原则/模型80/20principle80/20法则AAR-After Action Review行动后学习机制Ability Test能力测试Ability of Manager管理者的能力Absence Management缺勤管理Absence rate缺勤率Absent with leave因故缺勤(被)许可缺勤Absent without Leave无故缺勤擅离职守Absenteeism缺勤Accelerating Premium累进奖金制Accident Frequency事故频率Accident Insurance意外伤害保险Accident Investigation事故调查Accident Loss事故损失Accident Prevention事故预防Accident Proneness事故(频发)倾向Accident Severity事故严重程度Accident Severity Rate事故严重率Accident Work Injury工伤事故Achievement Need成就需求Achievement Test成就测试Action Learning行动(为)学习法Action Research行动研究Active Practice自动实习Adjourning解散期解散阶段Administer管理者Administrative Level管理层次Administrative Line直线式管理ADR-Alternative Dispute Resolution建设性争议解决方法Adventure learning探险学习法Adverse Impact负面影响Advertisement Recruiting广告招聘Affective Commitment情感认同Affiliation Need归属需求Affirmative Action反优先雇佣行动Age Composition年龄结构Age Discrimination年龄歧视Age Retirement因龄退休Agreement Content协议内容ALIEDIM费茨帕特里克出勤管理模型Allowance津贴Alternative Ranking Method交替排序法Amoeba Management变形虫式管理Analytic Approach分析法Annual Bonus年终分红Annual Leave年假Annuity/Pension退休金Applicant-Initiated Recruitment自荐式招聘Application Blank申请表Appraisal Feedback考评反馈Appraisal Interview考评面谈Appraisal Standardization考评标准化Appraiser Training考评者培训Apprenticeship Training学徒式培训Arbitration/Mediation仲裁Assessment Center评价中心ATS-Applicant Tracking System求职跟踪系统Attendance考勤Attendance Incentive Plan参与式激励计划Attendance Rate出勤率Attitude Survey态度调查Attribution Theory归因理论Audiovisual Instruction视听教学Authority职权Availability Analysis可获性分析Availability Forecast供给预测Background Investigation背景调查Balance-Sheet Approach决算表平衡法Bargaining Issue谈判问题BARS-Behaviorally Anchored Rating Scale Method行为锚定等级法Basic Skill基础技能Behavior Modeling行为模拟Behavior Modification行为矫正疗法Behavioral Description Interview工作方式介绍面试Behavioral Rating工作方式考核法BEI-behavior event interview行为事件访谈法Benchmark Job基准职位Benchmarking Management标杆管理Benefit Plan福利计划Benefit/Welfare福利BFOQ-Bona Fide Occupational Qualification实际职业资格Biological Approach生物型工作设计法Board Interview会议型面试BOS-Behavior Observation Scale行为观察量表Borter-Lawler's theory of Expectancy波特—劳勒期望激励理论Bottom-Line Concept底线概念Boundary less Organizational Structure无疆界组织结构Bounded Rationality有限理性Brainstorm Ideas头脑风暴法Broad banding Pay Structure扁平薪资结构BSC-balanced scorecard平衡计分卡Burnout精力耗尽Business Necessity经营上的必要性Cafeteria-Style Benefit自助式福利CAI-Computer-assisted Instruction电脑辅助指导Campus Recruiting校园招聘Candidate-Order Error侯选人次序错误Career Anchors职业锚/职业动机Career Counseling职业咨询Career Curve职业曲线Career Cycle职业周期Career Development Method职业发展方法Career Path职业途径Career Path Information职业途径信息Career Planning职业规划career plateau职业高原Career Stage职业阶段Career Training专业训练职业训练Career-Long Employment终身雇佣制Case Study Training Method案例研究培训法CBT-Computer Based Training以计算机为载体的培训Central Tendency居中趋势CIPP-Context, Input, Process, Product CIPP评估模型CIRO-ContextEvaluation,InputValuation,ReactionEvaluation,OutputEvaluationCIRO培训评估模式CIT-Critical Incident Technique关键事件技术Classification Method分类法Classroom Training课堂培训Closed Shop闭门企业CMI-Computer-managed Instruction电脑管理指导Coaching辅导教练Co-Determination共同决策制Coercive Power强制权力Cognitive Aptitude Test认知能力测试Cohesiveness凝聚力Colleague Appraisal同事考评Collective Bargaining劳资谈判Comparable Worth可比价值Comparative Appraisal Method比较评估法Compensable Factor报酬要素Compensation Benefit薪酬福利Compensation Committee报酬委员会Compensatory Time Off补假Competence-Based Interview基于能力的面试Competency Assessment能力评估Competency胜任特征Competency Model胜任特征模型Competency-Based Education and Training能力本位教育与训练Competency-Based Pay/Skill-Based Pay技能工资Complex情结Compressed Workweek压缩工作周Compulsory Binding Arbitration强制性仲裁Computerized Career Progression System电脑化职业生涯行进系统Computerized Forecast电脑化预测Conceptual Skill概念性技能Conciliation调解Concurrent Validity同期正当性Conference Method会议方法Conflict冲突Conflict Management冲突管理Construct Validity结构效度Constructive Discharge事实上的解雇Content Validity内容效度Contractual Right契约性权利Contras terror比较性错误Contributory Plan须付费的退休金计划Coordination Training合作培训Copayment共同付费Core Competency核心竞争力Core Value核心价值观Core Worker核心员工Core Workforce核心工作团队Corporate Culture企业文化Corporate Identity企业识别Corporate Image企业形象Correlation Analysis相关分析Cost Per Hire单位招聘成本Criterion-Related Validity标准关联效度Critical Job Dimension关键性工作因子Cross-Functional Training跨功能训练Cross-Training岗位轮换培训Culture Shock文化冲突Cumulative Trauma Disorder累积性工伤Cutoff Score录用分数线Cyclical Variation循环变动Decertification取消认可Defined Benefit Plan固定收益制Delphi Analysis德尔菲分析Deutero Learning再学习Differential Piece Rate差额计件工资Demission离职Demission Interview离职面谈Demission Rate离职率Disciplinary Action纪律处分Discriminate Analysis判别分析dismissal reason解雇理由disparate impact差别性影响disparate treatment差别性对待distribute bonus/profit-sharing分红distributive bargaining分配式谈判distributive justice分配公正diversity management多样性管理diversity training多样化培训division structure事业部结构Double-Loop Learning双环学习Downsizing裁员DTL-Decision Tree Induction决策树归纳法Dual Career Path双重职业途径dust hazard粉尘危害EAP-Employee Assistance Program员工帮助计划Early Retirement提前退休Early Retirement Factor提前退休因素Early Retirement Window提前退休窗口Earnings薪资Economic Strike经济罢工Education学历Education Subsidy教育津贴EEO-Equal Employment Opportunity公平就业机会EEOC-Equal Employment Opportunity Commission公平就业机会委员会Effect Factors of Career Planning职业规划影响因素Effect Factors of Development开发影响因素Effective Coaching Technique有效的训练方法Effective Working Hour有效工时Efficiency of Labor劳动效率Efficiency Wage效率工资Ego-Involvement自我投入E-Learning网络化学习Election Campaign选举活动Electronic Meeting电子会议Emotional Appeal感召力Employee Attitude Surveys员工态度调查Employee Career Management员工职业生涯管理Employee Consultation Services员工咨询服务Employee Equity员工公平Employee Leasing员工租借Employee Involvement员工参与Employee Manual员工手册Employee Orientation员工向导Employee Ownership员工所有制Employee Polygraph Protection Act《雇员测谎保护法案》[美] Employee Potential员工潜能Employee Referral在职员工推荐Employee Retirement Income Security Act《职工退休收入保障法》[美] Employee Safety and Health员工安全和健康Employee Security员工安全Employee Security Measures员工安全措施Employee Self-Service员工自助服务Employee Services Benefits员工服务福利Employee Skill员工技能Employee Stockownership Trust企业员工持股信托Employee Surplus员工过剩Employee Survey员工测评Employee Training Method员工培训方法Employee Turnover员工流动Employee Turnover Rate员工流动率Employee Under Training受训员工Employee-Centered Job Redesign以员工为中心的工作再设计Employees Bonus雇员红利Employer Unfair Labor Practices雇主不当劳动行为Employment雇用Employment Agency职业介绍所Employment Application Form应聘申请表Employment at will自由就业Employment Consultant招聘顾问Employment Contract Renewal雇用合同续签Employment Diseases职业病Employment History工作经历Employment Objective应聘职位Employment Offer/Enrollment录用Employment Relationship员工关系Employment Separation Certificate离职证明书Empowerment激励自主Entitlement授权法EQ-Emotional Quotient情感智商EPA-Equal Pay Act《平等工资法案》Equal Pay For Equal Work同工同酬Equity Theory公平理论E-Recruit网络招聘ERG theory ERG理论ERM-Employee Relationship Management员工关系管理ERP-Enterprise Resource Planning企业资源计划ESOP-Employee Stock Ownership Plan员工持股计划Essay Method叙述法ETS-Environmental Tobacco Smoke工作场所吸烟问题E-Survey电子调查Evaluation Criterion评价标准Excellent Leader优秀领导Executive Ability执行力Executive Compensation管理层薪资水平Executive Development Program主管发展计划Executive Director执行董事Executive Management行政管理Executive Marketing Director市场执行总监Executive Recruiters高级猎头公司Executive Salaries管理层工资Exempt Employee豁免员工Exit Interview离职面谈Expectancy Theory期望理论Expectation期望值Expected Salary期望薪水Experimental Method实验法Experimental Research试验调查Expiry of Employment雇用期满Exploit of HR人力资源开发External Costs外部成本External Employment外部招聘External Environment of HR人力资源外部环境External Equity外部公平External Labor Supply外部劳力供应External Recruiting Sources外部招聘来源External Recruitment Environment外部招聘环境Extra Work加班Extrinsic Rewards外部奖励Face Validity表面效度Factor Comparison Method因素比较法Fair Labor Standards Act《公平劳动标准法案》Family and Medical Leave Act《家庭和医疗假期条例》[美] Fiedler Contingency Model费德勒的权变模型First Impression Effect初次印象效应Five-Day Workweek每周五天工作制Fixed Term Appointment固定期聘用Fixed Term Contract固定任期合同Fixed Term Staff固定期合同工FJA-Functional Job Analysis功能性工作分析法Flat Organizational Structure扁平化组织结构Flex Place弹性工作地点Flex Plan弹性工作计划flextime弹性工作时间Flexible Benefits Program弹性福利计划Forced Distribution Method强制分配法Forced-Choice Method强迫性选择法Formal Organization正式组织Front-Line Manager基层管理人员Full-Time全职Function职能Function of HRM人力资源管理职能Functional Conflict Theory冲突功能理论Functional Department职能部门Funeral Leave丧假Fundamental Attribution Error基本归因误差Gain-Sharing Plan收益分享计划Gang Boss领班/小组长Gantt Charts甘特图GA TB-General Aptitude Test Battery普通能力倾向成套测验General Union总工会Given Role Playing角色定位演示法Glass Ceiling玻璃天花板Goal Conflict目标冲突GOJA-Guidelines Oriented Job Analysis指导性工作分析GoldenHandshake黄金握别Golden Parachute黄金降落伞Graphic Rating Scale图尺度评价法Grievance Mediation抱怨调解Grievance Procedure抱怨程序Gross Pay/Total Payroll工资总额Group Appraisal小组评价Group/Team Bonus团体/小组奖金Group Congeniality/Cohesiveness群体凝集力Group Life Insurance团体人寿保险Group Pension Plan团体退休金计划Group Piece Work集体计件制Guaranteed Employment Offer雇用信H? C? Gantt Premium System甘特奖励工资制Henderson Premium System艾末生奖励工资制Halo Effect晕轮效应Halseys Premium System哈尔赛奖励工资制Handwriting Analysis笔迹分析法Headhunting猎头Health Insurance健康保险H-Form/Holding Company H型结构Hierarchy of Needs Theory需要层次理论High-Performance Organization高绩效组织High-Performance Work System高绩效工作系统HMO-Health Maintenance Organization健康维护组织Holiday Pay假日薪水Home/Family Leave探亲假Horizontal Career Path横向职业途径Hot Stove Rule热炉规则Housing/Rental Allowance住房补贴HR Generalist人力资源通才HR Information System人力资源信息系统HR Manager人力资源经理HR Officer人力资源主任HR Policy人力资源政策HRCI-Human Resource Certification Institute人力资源认证机构HRD Appraisal人力资源开发评价HRD Intermediary人力资源开发媒介HRD Process人力资源开发过程HRD-Human Resource Development人力资源开发HRM-Human Resource Management人力资源管理HRP-Human Resource Planning人力资源规划Human Relations Movement人际关系运动Hygiene Factor保健因素Hypnosis催眠Ill-Health Retirement病退In-Basket Training篮中训练Incentive Compensation/Reward Payment/Premium奖金Incentive Plan激励计划Incentive-Suggestion System奖励建议制度Incident Process事件处理法Independent Contractor合同工Indirect Financial Compensation间接经济报酬Individual Incentive Plan个人奖金方案Individual Income Tax个人所得税Individual Interview个别谈话Individual Retirement Account个人退休账户Industrial Injury Compensation工伤补偿Industrial Union产业工会Informal Communication非正式沟通Informal Organization非正式组织In-House Training在公司内的培训Initial Interview初试Insurance Benefit保险福利Internal Environment of HR人力资源内部环境Internal Equity内部公平Internal Growth Strategy内部成长战略Internal Job Posting内部职位公开招聘Internal Recruitment内部招聘Internal Recruitment Environment内部招聘环境Interpersonal Skill人际交往能力Interview Appraisal面谈考评Interview Content面试内容Interview Method访谈法Interview Objective面试目标Interview Planning List面试计划表Intrinsic Reward内在奖励Jack Welch's Management韦尔奇式管理JAS-Job Analysis Schedule工作分析计划表Job工作、职业Job Account工作统计Job Action变相罢工(如怠工、放慢速度等) Job Aid工作辅助Job Assignment工作分配Job Analysis工作分析Job Analysis Formula工作分析公式Job Analysis Methods工作分析方法Job Analysis Information工作分析信息Job Analysis Process工作分析流程JAP-Job Analysis Program工作分析程序法Job Attitude工作态度Job Bidding竞争上岗Job Card工作单Job Characteristic工作因素Job Characteristics Model工作特性模式Job Classification职位分类Job Clinic职业问题咨询所Job Code工作编号,职位编号Job Context工作背景Job Description职位描述,工作说明Job Design工作设计Job Enlargement工作扩大化Job Enrichment工作丰富化Job Evaluation工作评估Job-Family工作群Job Identification工作识别Job Involvement工作投入Job Inventory工作测量表Job Knowledge Test业务知识测试Job Morale工作情绪Job Performance工作表现Job Plan工作计划Job Posting公开招聘Job Pricing工作定价Job Qualification and Restriction工作任职条件和资格Job Redesign工作再设计Job Rotation工作轮换Job Satisfaction工作满意度Job Security工作安全感Job Scope工作范围Job Sharing临时性工作分担Job Specialization工作专业化Job Specification工作要求细则Job Standard工作标准Job Stress工作压力Job Surrounding工作环境Job Time Card工作时间卡Job Vacancy职业空缺,岗位空缺Job-hop跳槽频繁者Job-posting system工作告示系统JTPA-Job Training Partnership Act《职业培训协作法》J? S? A dams Equity Theory亚当斯的公平理论Junior Board初级董事会Johari Window约哈瑞窗户Just Cause正当理由Karoshi过劳死Keogh Plan基欧计划KPI-key Process Indication企业关键业绩指标Kirkpatrick's Four-level Model of Evaluation四阶层评估模型Knowledge Database知识数据库Knowledge Management知识管理KSA-knowledge, skill, attitude知识,技能,态度Labor Clause劳工协议条款Labor Condition劳动条件Labor Contract劳动合同,雇佣合同Labor Contract Renewal劳动合同续签Labor Cost劳动成本Labor Demand Forecast劳动力需求预测Labor Discipline劳动纪律Labor Dispute劳动纠纷Labor Exchange/Employment Agency职业介绍所Labor Handbook劳动手册Labor Insurance劳保Labor Laws劳动法Labor Management Relations Act《劳动关系法》Labor Market劳动力市场Labor Protection劳动保护Labor Rate Variance工资率差异Labor Redundancies劳动力过剩Labor Relation劳动关系Labor Relation Consultant劳工关系顾问Labor Relations Process劳工关系进程Labor Reserve劳动力储备Labor Shortage劳动力短缺Labor Stability Index人力稳定指数Labor Wastage Index人力耗损指数Labor/Trade Union工会Labor/Working Hour人工工时Labor-Management劳动管理Lateral Communication横向沟通Lateral Thinking横向思维Layoff临时解雇Layoff Process临时解雇程序Leader Attach Training领导者匹配训练Leaderless Group Discussion无领导小组讨论法Leader-Member Exchange Theory领导者-成员交换理论Leader-Member Relation上下级关系Leader-Participation Model领导参与模式Leadership领导能力Learning Curve学习曲线Learning Organization学习型组织Learning Performance Test学习绩效测试Legitimate Power合法权力Level-to-Level Administration分级管理Life Cycle Theory of Leadership领导生命周期理论Life Insurance人寿保险Likes and Dislikes Survey好恶调查表Limitation Factors of PA考评的限制因素Line Manager直线经理Line Authority直线职权Line-Staff Relationship直线参谋关系Line Structure直线结构Loaned Personnel借调人员Lockout停工闭厂Locus of Control内外控倾向Long Term Trend长期趋势Long-Distance Education远程教育Long-Range Strategy长期策略Long-Term Contract长期合同Lower Management基层管理Lower-Order Need低层次需求Lump Sum Bonus/Pay Incentive绩效奖金Lump-Sum Merit Program一次性总付绩效报酬计划Managed Care有控制的医疗保健Management As Porpoise海豚式管理Management Assessment Center管理评价中心Management by Walking About走动管理Management Development管理层开发Management Development of IBMIBM的管理层开发Management of Human Resource Development人力资源开发管理Management Psychology管理心理学Management Right管理权Management Risk管理风险Management Tool管理工具Management Training管理培训Managerial Art管理艺术Managerial Authority管理权威Managerial Function管理职能Managerial Grid Theory管理方格理论Mandated Benefit强制性福利Mandatory Bargaining Issue强制性谈判项目Marital Status婚姻状况Market Price市场工资Markov Analysis马尔可夫分析过程Marriage Leave婚假Massed Practice集中练习集中学习Matrix Structure矩阵结构MBO-Management By Objective目标管理MBTI-Myers-Briggs Type Indicator迈尔斯—布里格个性类型测量表Mc-Clelland's Theory of Needs麦克里兰需要理论McDonnell-Douglas Test麦当纳道格拉斯法Mechanistic Approach机械型工作设计法Mediator/Negotiator调解人Medical Insurance医疗保险Medical/Physical Ability Inspection/Physical Ability Test体检Membership Group实属群体Mental Ability Test逻辑思维测试Mentor指导者Mentoring辅导制Mentoring Function指导功能Merit Pay绩效工资Merit Raise绩效加薪Metrics-Driven Staffing Model标准驱动招聘模式Mid-Career Crisis Sub Stage中期职业危机阶段Minimum Wage最低工资Mission Installation Allowance出差津贴Mixed-Standard Scale Method多重标准尺度法Motivation激励Motivational Approach激励型工作设计法Motivational Factor激励因素Motivational Pattern激励方式Motivation-hygiene Theory激励保健论MPS-Motivating Potential Score激励潜能分数Multidivisional Structure M型结构Multimedia Technology多媒体技术Multiple Cutoff Model多切点模式Multiple Hurdle Model跨栏模式National Culture民族文化National Union(国家)总工会Needs Assessment需求评估Negligent Hiring随意雇佣Nepotism裙带关系Network Career Path网状职业途径Networking网络化(组织)NGT-Nominal Group Technique群体决策法No Financial Compensation非经济报酬Noncontributory Plan非付费退休金计划Nondirective Interview非定向面试Nondiscrimination Rule非歧视性原则Nonexempt Employee非豁免的员工Nonverbal Communication非言语沟通No-Pay Study Leave无薪进修假期Normal Retirement正常退休Normative Analysis规范分析法。
现代大学英语中级写作课程教案Document serial number【KKGB-LBS98YT-BS8CB-BSUT-BST108】《现代大学英语中级写作》,徐克容,外语教学与研究出版社英语写作中级(上)课程教案I 授课题目:Unit One We Learn As We Grow一、教学目的、要求:(一)掌握:1、To learn the basics of exemplication:→ Definition→ Kinds of examples→ Sources of examples2、To learn to outline expositive essays知识点:→ The definition and introduction of exposition and essay.→Exposition is explanatory writing. It’s purpose is toexplain or clarify a point.→ An essay is a related group of paragraphs written for some purpose(二)熟悉:→ Practice the basics of exemplification→ Practice outlining知识点:→ Patterns of exposition, the choice of examples, the choice of appropriate examples, the organization of anexemplification essay:→Types of essays, basic structures of an expositive essay, elements of the expositive essay→ Types of outline, rules concerning outline(三)了解:→Patterns of exposition, types of essays, types of outlineprocess analysis, cause-effect analysis, Comparisonand contrast, classification, definition andanalogy, narrative essays, descriptive essays,expositive essays and argumentative essays二、教学重点及难点:重点:Exemplification, types of outline;难点:Sentence outline and topic outline三、课时安排:共4课时四、授课方式:讲授、课堂快速阅读练习、课堂提问、写作实践讲解五、教学基本内容第一课 Exemplification第一课Elements of the Essay: Outlining六、参考书目:《英语写作手册》,《美国大学英语写作》七、作业和思考题:第一次:Read on the subject and write an example paper of 200-250 words on the given topic.第二次:Read on the subject and write an essay of 200-250 words on the given topic, using either a single extended example or two or three short ones to develop your thesis statement.第三次: Ask students to practice outlining八、课后小结:Emphasis on the writing procedure→ Prewriting-choosing a topic and exploring ideas→ Drafting: getting your ideas on paper→ Revising: strengthening your essay→ Editing and proofreading: eliminating technical errorsII授课题目:Unit Two I Made It一、教学目的、要求:(一)掌握:1、To learn the basics of process analysis→ Definition→ Uses→ Types→ Methods2、To learn to write thesis statement知识点:→ The definiton and introduction of process analysis→ The function of process analysis→ The differences between thesis statement vs. topic sentence(二)熟悉:→ The areas the process analysis is usually used.知识点: → Functions of process analysis:giving instructions, giving information and giving the history→ Major types of process analysis: directive analysis, informative process analysis→ Writing an effective thesis statement(三)了解:The basics of process writing and thesis statement二、教学重点及难点:重点:Organization of a process paper, practice of effective thesis statement;难点:Guidelines on process analysis, writing effective thesis ststement三、课时安排:共4课时四、授课方式:讲授、课堂快速阅读练习、课堂提问、写作实践讲解五、教学基本内容第二课 Process Analysis第二课 Elements of the essay: The Thesis Statement六、参考书目:《英语写作手册》,《美国大学英语写作》七、作业和思考题:第一次:Read on the subject and write an informative process paper describing how you succeeded in doing something第二次:Read on the subject and write a directive process paper telling first-year students how to adjust to life at college. 第三次:Ask students to practise writing the thesis statement八、课后小结:Emphasis on the writing procedure→ Prewriting-chossing a topic and exploring ideas→ Drafting:getting your ideas on paper→ Revising: strengthening your essay→ Editing and proofreading: eliminating technical errors授课题目:Unit Three College Is Not a Paradise一、教学目的、要求:(一)掌握:1、To learn the basics of Cause-Effect analysis→ Definition→ Uses→ Patterns2、To learn to write an introduction to expositive essays→ What to include in the introduction→ How to write effective introduction知识点:→ The definiton and introduction of cause-effect analysis → The function of cause-effect analysis→ The writing of effective introduction(二)熟悉:→ The functions and areas the cause-effect analysis is usually used.知识点: → Functions of cause-effect analysis: explaining why certain things happen, analyzing what will happen as a result → Major types of cause-effect analysis: focusing on cause and focusing on effects,→ How to start and write effective introduction(三)了解: the basics of cause-effect analysis and writing effective introduction二、教学重点及难点:重点:How to focus on cause or effects, How to start and write effective introduction;难点:How to focus on cause or effects, How to start and write effective introduction三、课时安排:共4课时四、授课方式:讲授、课堂快速阅读练习、课堂提问、写作实践讲解五、教学基本内容第三课 Cause-Effect Analysis第三课 Parts of the essay: The Introduction六、参考书目:《英语写作手册》,《美国大学英语写作》七、作业和思考题:第一次:Read on the subject and write an essay on any of the given topics analyzing cause.第二次:Read on the subject and write, from your own experience, an essay analyzing the effects of anthing taught in class.第三次:Ask students to practise writing the introduction八、课后小结:Emphasis on the writing procedure→ Prewriting- chossing a topic and exploring ideas→ Drafting: getting your ideas on paper→ Revising: strengthening your essay→ Editing and proofreading: eliminating technical errors授课题目:Four What Makes the Differences一、教学目的、要求:(一)掌握:1、To learn the basics of Comparison and Contrast→ Definition→ Uses→ Patterns→ Methods2、To learn to develop the body of expositive essays→ What its structure looks like?→ What it includes知识点:→ The definiton and introduction of Comparison and Contrast → The function of cause-effect analysis→ The writing of effective introduction(二)熟悉:→ The functions and areas the comparison/contrast is usually used., the general structure of the body ofan essay知识点: → Functions of comparison/contrast: clarifying something unknown, bringing one or both of the subject intosharper shape→ Three patterns of comparison/contrast: subject bysubject, point by point, mixed sequence→ Familiarity of the general structure of the body of an essay(三)了解: The basics of Comparison and Contrast and the general structure of the body of an essay二、教学重点及难点:重点:Three patterns of comparison/contrast: subject by subject, point by point, mixed sequenceGeneral structure of the body: Beginning, Body and End难点: How to organize a comparison/contrast essay, How to develop body paragraphs三、课时安排:共4课时四、授课方式:讲授、课堂快速阅读练习、课堂提问、写作实践讲解五、教学基本内容第四课 Comparison/Contrast第四课 Parts of the essay: The Body六、参考书目:《英语写作手册》,《美国大学英语写作》七、作业和思考题:第一次:Read on the subject and write a subject-by-subject essay of comparison/contraston any of the given topics第二次:Read on the subject and write a point -by-point essay of comparison/contraston any of the given topics第三次:Ask students to practise writing the body of the essay 八、课后小结:Emphasis on the writing procedure→ Prewriting-chossing a topic and exploring ideas→ Drafting:getting your ideas on paper→ Revising: strengthening your essay→ Editing and proofreading: eliminating technical errors授课题目:Unit Five It Takes All Sorts to Make a World一、教学目的、要求:(一)掌握:1、To learn the basics of Classification→ Definition→ Uses→ Methods2、To learn to write the conclusion of expositive essays→ What is classification?→ What is classification used for?知识点:→ The definiton and introduction of classification→ The function of classification→ The writing of effective classification(二)熟悉:→ The functions and areas the classification is usually used., the conclusion of expositive essays知识点: → Functions of classification:To organize and perceive the world around usTo present a mass of material by means of some orderly systemTo deal with complex or abstract topics by breaking a broad subject into smaller, neatly sorted categories.→ The general pattern of classification→ sentence patterns in classification→ Familiarity of the the conclusion of expositive essays (三)了解: The functions and areas the classification is usually used., the conclusion of expositive essays二、教学重点及难点:重点:some sentence patterns in classificationthe conclusion of expositive essays难点: Parts of the conclusion: a summary of the main points, or restatements of your thesis in different work.三、课时安排:共4课时四、授课方式:讲授、课堂快速阅读练习、课堂提问、写作实践讲解五、教学基本内容第五课 classification第五课 Parts of the essay: The conclusion六、参考书目:《英语写作手册》,《美国大学英语写作》七、作业和思考题:第一次:Read on the subject and write a classification essay on any of the given topics第二次:Write an essay of 200-250 words on any of the given topics. 第三次:Ask students to practise writing the conclusion of the essay 八、课后小结:Emphasis on the writing procedure→ Prewriting-chossing a topic and exploring ideas→ Drafting:getting your ideas on paper→ Revising: strengthening your essay→ Editing and proofreading: eliminating technical errors授课题目:Unit Six What Does It Mean一、教学目的、要求:(一)掌握:1、To learn the basics of Definition→ Definition→ Types→ Methods of Organization2、To learn to write the title of expositive essays→ What is definiton→ Types of definition知识点:→ The Standard /Formal Definition→ The Connotative/Personal Definition→ The Extended Definition(二)熟悉:→ The functions and areas the definition is usuallyused., the title of expositive essays知识点: → Functions and patterns of definition:→ The Standard /Formal Definition is used to explain a term or concept your audience or reader may not know orunderstand,→ The Connotative/Personal Definition is used to explain any word or concept that doesn’t have the same meaningfor everyone.→ The Extended Definition is used to explore a topic by examining its various meanings and implications.(三)了解: How to write an extended definitionHow to organize an extended essay二、教学重点及难点:重点:Functions and patterns of definitionHow to write an extended definitionHow to write the title of an expositive essay难点:How to organize an extended essayHow to write the title of an expositive essay三、课时安排:共4课时四、授课方式:讲授、课堂快速阅读练习、课堂提问、写作实践讲解五、教学基本内容第六课 definition第六课 Parts of the essay: The Title六、参考书目:《英语写作手册》,《美国大学英语写作》七、作业和思考题:第一次: Read on the subject and write a definition essay on any of the given topics第二次:Write an essay of 200-250 words on any of the given topics. 第三次:Ask students to practise writing the title of the essay八、课后小结:Emphasis on the writing procedure→ Prewriting- choosing a topic and exploring ideas→ Drafting: getting your ideas on paper→ Revising: strengthening your essay→ Editing and proofreading: eliminating technical errorsUnit Six Task One DefinitionI What is definition?In talking with other people, we sometimes offer informal definitions to explain just what we mean by a particular term. That is, to avoid confusion or misunderstanding, we have to define a word, term, or concept which is unfamiliar to most readers or open to various interpretations.Suppose, for example, we say to a friend:” Forrest is really an inconsiderate person.” We might then explain what we mean by“ inconsiderate” by saying, “He borrowed my accounting book overnight but didn’t return it for a week. And when I got it back,it was covered with coffee stains.Definition is the explanation of the meaning of a word or concept, and it is also a method of developing an essay.II. The ways to define a word or termThere are three basic ways to define a word or termA. To give a synonym For example: ‘ To mend is to repair.” Or“ A fellow is a man or a boy.”B. To use a sentence (often with an attributive clause) For example,ink may be define in a sentence: “Ink is colored water which we use for writing.”C. To write a paragraph or even an essay But a synonymy or asentence cannot give a satisfactory definition of an abstract term whose meaning is complex. We have to write a paragraph or an essay with examples or negative examples (what the term does not mean),with analogies or comparisons, with classification or cause-effect analysis.III. When we give a definition, we should observe certain principles: 1.First, we should avoid circular definitions. “Democracy is thedemocratic process.” And “astronomer is one who studiesastronomy” are circular definition.2.Second, we should avoid long lists of synonyms if the term to bedefined is an abstract one. For example: By imagination, I meanthe power to form mental images of objects, the power to form new ideas, the gift of employing images in writing, and the tendency to attribute reality to unreal things, situations and states.(picking up words, expressions from a dictionary , in the hopethat one will hit)3.Third, we should avoid loaded definition, Loaded definitions donot explain terms but make an immediate appeal for emotionalapproval.A definition like:’ By state enterprise, I mean high cost andpoor efficiency.” is loaded with pejorative emotionalconnotation. Conversely, “ By state enterprise, I mean one ofthe great blessing of democratic planning” is loaded withfavorable emotional connotation. Such judgements can be vigorious to a discussion, but they lead to argument, not clarification,when offered as definition.IV. Types of definition1.Standard/ Formal definition---denotation is a word’s core, direct,and literal meaning.2.Connotative/Personal meaning---Explains what you mean by a certainterm or concept that could have different meanings for others.On the other hand, connotation is the implied, suggested meaning of a word; it refers to the emotional response stimulated byassociations the word carries with it.A.For Americans, Water gate is associated with a politicalscandal that means dishonesty. And more words are created with the suffix—gate to mean some scandal in English now, thus,Iran Gate, Intelligence GateB.Dogs, in Chinese culture, may be quite a negative image. It isinsulting to call someone a dog. What about the western people In their eyes, dog is lovely and has good associated meanings.They say “ Love me, love my dog.”C.Imperialism means to us Chinese quite negative. Some of thewestern people may be proud of being imperial and imperialismitself.D.People everywhere may also share some connotations for somewords. They are general connotations. Mother means love, care, selfless, etc.E.Let’s get the gang together for a party tonight. (a group)Don’t go around with that gang or you’ll come to no good.(degraded group of people or group of criminals)Connotation can make all the difference. It is the mirror ofyour attitude.3.Extended definition---is an essay length piece of writing usingthis method of development.V. How to write an extended definitionFollow 4 rules for a good definition:1. Don’t use the words “when “‘where”, giving a definition. A commonpractice is to define the noun with a noun, adjective with adjective and so on.2. Remember, that definition is not a repetition.3. Use simple and well- known term in your explanation.4. Point out the distinguishing features of the term.Unit Six Task Two: The TitleI.What is title?A title is a very brief summary of what your paper is about.It is often no more than several words. You may find it easierto write the title after you have completed your paper.A title may be a phrase which can indicate a topic ofinterest (i.e. your focus) and at the same time point towardsa particular kind of discussion (your mode of argument).Accordingly, your title needs not only to indicate what theessay will be about, but also to indicate the point of view itwill adopt concerning whatever it is about.II.The purpose of the titleTo give the reader an idea of what the essay is aboutTo provide focus for the essayTo arouse the reader’s interestIII.How to write a good titleMake it clear, concise and preciseUse a phrase rather than a sentenceExclude all extra wordsIV.Other rules to obeyCenter it at the top of the first page.Use no period at the end or quotation marksCapitalize the first and last wordsCapitalize all other words exceptarticles (a, the)the to in infinitivesprepositions containing one syllablecoordinating conjunctions (and, but, or, etc)A title leads, but a poor title misleads. Be sure that it is appropriate. Besides, be careful with the capitalization.Write an appropriate title for each of the introductory paragraphs that follow.1.Title: _____Reactions to Disappointment___________________Ben Franklin said that the only sure things in life are deathand taxes. He left something out, however: disappointment. Noone gets through life without experiencing many disappointments.Strangely, though, most people seem unprepared fordisappointment and react to it in negative ways. They feeldepressed or try to escape their troubles instead of usingdisappointments asan opportunity for growth.2.Title: ____Annoying People_____________________President Richard Nixon used to keep “enemies list” of all the people he didn’t especially like. Iam ashamed to confess it,butI, too, have an enemies list—a mental one. On this list are the people I would gladly live without , the ones who cause my blood pressure to rise to the boiling point. The top threeplaces on the list go to people with annoying nervous habits,people who talk in movie theatres, and people who talk on carphones while driving.3.Title: ___The Meaning of Maturity______________________Being a mature student does not mean being an old-timer.Maturity is not measured by the number of years a person havelived. Instead, the yardstick of maturity is marked by thequalities of self-denial, determination, and dependability.4.Title: _____College Stress____________________Jack’s heart pounds as he casts panicky looks around theclassroom. He doesn’t recognize the professor, he doesn’t know any of the students, and he can’t even figure out what thesubject is. In front of him is a test. At the last minute hisroommate awakens him. It’s only another anxiety dream. The very fact that dreams like Jack’s are common suggests that college is a stressful situation for young people. The cause of thisstress can be academic, financial, and personal.5.Title: __How to Complain_______________________I’m not just a consumer—I’m a victim. If I order a product, it is sure to arrive in the wrong color, sixe, or quantity. If I hire people to do repairs, they never arrive on the dayscheduled. If I owe a bill, the computer is bound to overcharge me. Therefore, in self-defense, I have developed the following consumer’s guide to complaining affectively授课题目:Unit Seven The Insight I Gained 一、教学目的、要求:(一)掌握:1、To learn the basics of Analogy→ Definition→ Uses→ Methods of Organization2、To learn to use transitions→ What is analogy→ The difference between analogy and comparison知识点:→ The field analogy is used→ The difference between analogy and comparison→ The patterns of analogy(二)熟悉:→ The functions and areas analogy is usually used., to learn to use transition知识点: → Functions and patterns of analogy:→ A comparison explains two obviously similar things and considers both their differences and similarities→ An analogy compares two apparently unlike things, and focus only on their major similarities→ An analogy is thus an extended metaphor—the figure of speech that declares one thing to be another(三)了解: How to organize an analogy by the way ---subject bysubjectHow to organize an analogy by the way—point by point 二、教学重点及难点:重点:Functions and patterns of definitionThe differences between comparison and analogyHow to learn to use transitionHow to organize an analogy by the way ---subject by subject How to organize an analogy by the way—point by point难点:How to learn to use transitionHow to organize an analogy by the way ---subject by subject How to organize an analogy by the way—point by point三、课时安排:共4课时四、授课方式:讲授、课堂快速阅读练习、课堂提问、写作实践讲解五、教学基本内容第六课 definition第六课 Parts of the essay: The Title六、参考书目:《英语写作手册》,《美国大学英语写作》七、作业和思考题:第一次: Read on the subject and write a definition essay on any of the given topics第二次:Write an essay of 200-250 words on any of the given topics. 第三次:Ask students to practise writing the title of the essay八、课后小结:Emphasis on the writing procedure→ Prewriting-chossing a topic and exploring ideas→ Drafting: getting your ideas on paper→ Revising: strengthening your essay→ Editing and proofreading: eliminating technical errors。
Effective Utterance Classification with Unsupervised Phonotactic ModelsHiyan Alshawi AT&T Labs -Research Florham Park,NJ 07932,USA hiyan@AbstractThis paper describes a method for utterance classification that does not require manual transcription of training data.The method combines domain independent acoustic models with off-the-shelf classifiers to give utterance classification performance that is surprisingly close to what can be achieved using conven-tional word-trigram recognition requiring man-ual transcription.In our method,unsupervised training is first used to train a phone n-gram model for a particular domain;the output of recognition with this model is then passed to a phone-string classifier.The classification ac-curacy of the method is evaluated on three dif-ferent spoken language system domains.1IntroductionA major bottleneck in building data-driven speech pro-cessing applications is the need to manually transcribe training utterances into words.The resulting corpus of transcribed word strings is then used to train application-specific language models for speech recognition,and in some cases also to train the natural language components of the application.Some of these speech processing ap-plications make use of utterance classification,for exam-ple when assigning a call destination to naturally spoken user utterances (Gorin et al.,1997;Carpenter and Chu-Carroll,1998),or as an initial step in converting speech to actions in spoken interfaces (Alshawi and Douglas,2001).In this paper we present an approach to utterance clas-sification that avoids the manual effort of transcribing training utterances into word strings.Instead,only the desired utterance class needs to be associated with each sample utterance.The method combines automatic train-ing of application-specific phonotactic models togetherwith token sequence classifiers.The accuracy of this phone-string utterance classification method turns out to be surprisingly close to what can be achieved by conven-tional methods involving word-trigram language mod-els that require manual transcription.To quantify this,we present empirical accuracy results from three differ-ent call-routing applications comparing our method with conventional utterance classification using word-trigram recognition.Previous work at AT&T on utterance classification without words used information theoretic metrics to dis-cover “acoustic morphemes”from untranscribed utter-ances paired with routing destinations (Gorin et al.,1999;Levit et al.,2001;Petrovska-Delacretaz et al.,2000).However,that approach has so far proved impractical:the major obstacle to practical utility was the low run-time detection rate of acoustic morphemes discovered during training.This led to a high false rejection rate (be-tween 40%and 50%for 1-best recognition output)when a word-based classification algorithm (the one described by Wright et.al (1997))was applied to the detected se-quence of acoustic morphemes.More generally,previous work using phone string (or phone-lattice)recognition has concentrated on tasks in-volving retrieval of audio or video (Jones et al.,1996;Foote et al.,1997;Ng and Zue,1998;Choi et al.,1999).In those tasks,performance of phone-based systems was not comparable to the accuracy obtainable from word-based systems,but rather the rationale was avoiding the difficulty of building wide coverage statistical language models for handling the wide range of subject matter that a typical retrieval system,such as a system for retrieving news clips,needs to cover.In the work presented here,the task is somewhat different:the system can automatically learn to identify and act on relatively short phone subse-quences that are specific to the speech in a limited domain of discourse,resulting in task accuracy that is comparable to word-based methods.Edmonton, May-June 2003Main Papers , pp. 1-7 Proceedings of HLT-NAACL 2003In section2we describe the utterance classification method.Section3describes the experimental setup and the data sets used in the experiments.Section4presents the main comparison of the performance of the method against a“conventional”approach using manual tran-scription and word-based models.Section5gives some concluding remarks.2Utterance Classification Method2.1Runtime OperationThe runtime operation of our utterance classification method is simple.It involves applying two models (which are trained as described in the next subsection):A statistical n-gram phonotactic model and a phone string classification model.At runtime,the phonotactic model is used by an automatic speech recognition system to con-vert a new input utterance into a phone string which is mapped to an output class by applying the classification model.(We will often refer to an output class as an“ac-tion”,for example transfer to a specific call-routing des-tination).The configuration at runtime is as shown in Figure1.More details about the specific recognizer and classifier components used in our experiments are given in the Section3.Figure1:Utterance classifier runtime operation The classifier can optionally make use of more infor-mation about the context of an utterance to improve the accuracy of mapping to actions.As noted in Figure1, in the experiments presented here,we use a single addi-tional feature as a proxy for the utterance context,specif-ically,the identity of the spoken prompt that elicited the utterance.It should be noted,however,that inclusion of such additional information is not central to the method: Whether,and how much,context information to include to improve classification accuracy will depend on the ap-plication.Other candidate aspects of context may include the dialog state,the day of week,the role of the speaker, and so on.2.2Training ProcedureTraining is divided into two phases.First,train a phone n-gram model using only the training utterance speech files and a domain-independent acoustic model.Second, train a classification model mapping phone strings and prompts(the classifier inputs)to actions(the classifier outputs).The recognition training phase is an iterative proce-dure in which a phone n-gram model is refined succes-sively:The phone strings resulting from the current pass over the speechfiles are used to construct the phone n-gram model for the next iteration.In other words,this is a“Viterbi re-estimation”or“1-best re-estimation”pro-cess.We currently only re-estimate the n-gram model,so the same general-purpose HMM acoustic model is used for ASR decoding in all iterations.Other more expen-sive n-gram re-estimation methods can be used instead, including ones in which successive n-gram models are re-estimated from n-best or lattice ASR output.Candi-dates for the initial model used in this procedure are an unweighted phone loop or a general purpose phonotactic model for the language being recognized.The steps of the training process are as follows.(The procedure is depicted in Figure2.)Figure2:Utterance classifier training procedure1.Set the phone string model G to an initial phonestring model.Initialize the n-gram order N to1.(Here‘order’means the size of the n-grams,so for example2means bi-grams.)2.Set S to the set of phone strings resulting from rec-ognizing the training speechfiles with G(after pos-sibly adjusting the insertion penalty,as explained below).3.Estimate an n-gram model G of order N from theset of strings S.4.If N<N max,set N←N+1and G←G and goto step2,otherwise continue with step5.5.For each recognized string s∈S,construct a clas-sifier input pair(s,r)where r is the prompt that elicited the utterance recognized as s.6.Train a classification model M to generalize thetraining function f:(s,r)→a,where a is the action associated with the utterance recognized as s.7.Return the classifier model M and thefinal n-grammodel G as the results of the training procedure. Instead of increasing the order N of the phone n-gram model during re-estimation,an alternative would be to iterate N max times with afixed n-gram order,possibly with successively increased weight being given to the lan-guage model vs.the acoustic model in ASR decoding. One issue that arises in the context of unsupervised recognition without transcription is how to adjust recog-nition parameters that affect the length of recognized strings.In conventional training of recognizers from word transcriptions,a“word insertion penalty”is typ-ically tuned after comparing recognizer output against transcriptions.To address this issue,we estimate the ex-pected speaking rate(in phones per second)for the rele-vant type of speech(human-computer interaction in these experiments).The token insertion penalty of the recog-nizer is then adjusted so that the speaking rate for auto-matically detected speech in a small sample of training data approximates the expected speaking rate.3Experimental Setup3.1DataThree collections of utterances from different domains were used in the experiments.Domain A is the one stud-ied in previously cited experiments(Gorin et al.,1999; Levit et al.,2001;Petrovska-Delacretaz et al.,2000).Ut-terances for domains B and C are from similar interactive spoken natural language systems.Domain A.The utterances being classified are the cus-tomer side of live English conversations between AT&T residential customers and an automated customer care system.This system is open to the public so the num-ber of speakers is large(several thousand).There were 40106training utterances and9724test utterances.The average length of an utterance was11.29words.The split between training and test utterances was such that the ut-terances from a particular call were either all in the train-ing set or all in the test set.There were56actions in this domain.Some utterances had more than one action associated with them,the average number of actions as-sociated with an utterance being1.09.Domain B.This is a database of utterances from an in-teractive spoken language application relating to product line information.There were10470training utterances and5005test utterances.The average length of an utter-ance was3.95words.There were54actions in this do-main.Some utterances had more than one action associ-ated with them,the average number of actions associated with an utterance being1.23.Domain C.This is a database of utterances from an interactive spoken language application relating to con-sumer order transactions(reviewing order status,etc.)in a limited domain.There were14355training utterances and5000test utterances.The average length of an utter-ance was8.88words.There were93actions in this do-main.Some utterances had more than one action associ-ated with them,the average number of actions associated with an utterance being1.07.3.2RecognizerThe same acoustic model was used in all the experiments reported here,i.e.for experiments with both the phone-based and word-based utterance classifiers.This model has42phones and uses discriminatively trained3-state HMMs with10Gaussians per state.It uses feature space transformations to reduce the feature space to60fea-tures prior to discriminative maximum mutual informa-tion training.This acoustic model was trained by Andrej Ljolje and is similar to the baseline acoustic model used for experiments with the Switchboard corpus,an earlier version of which is described by Ljolje et al.(2000). (Like the model used here,the baseline model in those experiments does not involve speaker and environment normalizations.)The n-gram phonotactic models used were represented as weightedfinite state automata.These automata(with the exception of the initial unweighted phone loop)were constructed using the stochastic language modeling tech-nique described by Riccardi et al.(1996).This modeling technique,which includes a scheme for backing off to probability estimates for shorter n-grams,was originally designed for language modeling at the word level.3.3ClassifierDifferent possible classification algorithms can be used in our utterance classification method.For the experiments reported here we use the BoosTexter classifier(Schapire and Singer,2000).Among the alternatives are decision trees(Quinlan,1993)and support vector machines(Vap-nik,1995).BoosTexter was originally designed for text categorization.It uses the AdaBoost algorithm(Freund and Schapire,1997;Schapire,1999),a wide margin ma-chine learning algorithm.At training time,AdaBoost selects features from a specified space of possible fea-tures and associates weights with them.A distinguishing characteristic of the AdaBoost algorithm is that it places more emphasis on training examples that are difficult to classify.The algorithm does this by iterating through a number of rounds:at each round,it imposes a distribu-tion on the training data that gives more probability mass to examples that were difficult to classify in the previ-ous round.In our experiments,500rounds of boosting were used;each round allows the selection of a new fea-ture and the adjustment of weights associated with exist-ing features.In the experiments,the possible features are identifiers corresponding to prompts,and phone n-grams or word n-grams(for the phone and word-based methods respectively)up to length4.3.4Experimental ConditionsThree experimental conditions are considered.The suf-fixes(M and H)in the condition names refer to whether the two training phases(i.e.training for recognition and classification respectively)use inputs produced by ma-chine(M)or human(H)processing.PhonesMM This experimental condition is the method described in this paper,so no human transcriptions are used.Unsupervised training from the training speechfiles is used to build a phone recognition model.The classifier is trained on the phone strings resulting from recognizing the training speechfiles with this model.At runtime,the classifier is ap-plied to the results of recognizing the testfiles with this model.The initial recogition model for the un-supervised recognition training process was an un-weighted phone loop.Thefinal n-gram order used in the recognition training procedure(N max in sec-tion2)was5.WordsHM Human transcriptions of the training speech files are used to build a word trigram model.The classifier is trained on the word strings resulting from recognizing the training speechfiles with this word trigram model.At runtime,the classifier is ap-plied to the results of recognizing the testfiles with the word trigram model.Learned phone Correspondingsequence wordsk ao l z callsn ah m b numb erf aa n phoner ey t ratek ae n s canc elaa p ax r oper atoraw t m ay what mych eh k checkm ay b my b illp ae n ih com panys w ih ch switcher n ae sh int ernat ionalv ax k w ha ve a que stionl ih ng p bil ling p lanr ey t s ratesk t uw p li ke to p ayae l ax n b alan cem er s er custo mer ser vicer jh f ao cha rge fo rTable1:Example phone sequences learned by the train-ing procedure from domain A training speechfiles. WordsHH Human transcriptions of the training speech files are used to build a word trigram model.The classifier is trained on the human transcriptions of the speech trainingfiles.At runtime,the classifier is applied to the results of recognizing the testfiles with the word trigram model.For all three conditions,median recognition and classi-fication time for test data was less than real time(i.e.the duration of test speechfiles)on current micro-processors. As noted earlier,the acoustic model,the number of boost-ing rounds,and the use of prompts as an additional clas-sification feature,are the same for all experimental con-ditions.3.5Example learned phone sequencesTo give an impression of the kind of phone sequences resulting from the automatic training procedure and ap-plied by the classifier at runtime,see Table1.The table lists some examples of such phone strings learned from domain A training speechfiles,together with English words,or parts of words(shown in bold type),they may correspond to.(Of course,the words play no part in the method and are only included for expository purposes.) The phone strings are shown in the DARPA phone alpha-bet.Rejection PhoneMM WordHM WordHHrate(%)accuracy accuracy accuracy 1079.581.181.52084.485.886.23089.490.590.94094.194.794.45097.297.396.7Table2:Phone-based and word-based utterance classifi-cation accuracy for domain A4Classification AccuracyIn this section we compare the accuracy of our phone-string utterance classification method(PhonesMM)with methods(WordsHM and WordsHH)using manual tran-scription and word string models.Accuracy MetricThe results are presented as utterance classification rates, specifically the percentage of utterances in the test set for which the predicted action is valid.Here a valid predic-tion means that the predicted action is the same as one of the actions associated with the test utterance by a human labeler.(As noted in section3,the average number of actions associated with an utterance was1.09,1.23,and 1.07for domains A,B,and C,respectively.)In this met-ric we only take into account a single action predicted by the classifier,i.e.this is“rank1”classification ac-curacy,rather than the laxer“rank2”classification ac-curacy(where the classifier is allowed to make two pre-dictions)reported by Gorin et.al(1999)and Petrovska et.al(2000).In practical applications of utterance classification, user inputs are rejected if the confidence of the classifier in making a prediction falls below a threshold appropri-ate to the application.After rejection,the system may, for example,route the call to a human or reprompt the user.We therefore show the accuracy of classifying ac-cepted utterances at different rejection rates,specifically 0%(all utterances accepted),10%,20%,30%,40%,and 50%.Following Schapire and Singer(2000),the con-fidence level,for rejection purposes,assigned to a pre-diction is taken to be the difference between the scores assigned by BoosTexter to the highest ranked action(the predicted action)and the next highest ranked action. Accuracy ResultsUtterance classification accuracy rates,at various rejec-tion rates,for domain A are shown in Table2for the three experimental conditions described in section3.4. The corresponding results for domains B and C are shown in Tables3and4.Rejection PhoneMM WordHM WordHHrate(%)accuracy accuracy accuracy 1086.086.785.32090.090.689.53093.993.792.34096.396.894.75097.597.796.4Table3:Phone-based and word-based utterance classifi-cation accuracy for domain BRejection PhoneMM WordHM WordHHrate(%)accuracy accuracy accuracy 068.268.969.91073.373.774.92078.979.280.23084.884.785.54089.789.390.25094.193.394.5Table4:Phone-based and word-based utterance classifi-cation accuracy for domain CThe utterances in domain A are on average longer and more complex than in domain B;this may partly explain the higher classification rates for domain B.The gener-ally lower classification accuracy rates for domain C may reflect the larger set of actions for this domain(92ac-tions,compared with56and54actions for domains A and B).Another difference between the domains was that the recording quality for domain B was not as high as for domains A and C.Despite these differences between the domains,there is a consistent pattern for the compar-ison of most interest to this paper,i.e.the relative per-formance of utterance classification methods requiring or not requiring transcription.Perhaps the most surprising outcome of these ex-periments is that the phone-based method with short “phrasal”contexts(up to four phones)has classifica-tion accuracy that is so close to that provided by the longer phrasal contexts of trigram word recognition and word-string classification.Of course,the re-estimation of phone n-grams employed in the phone-based method means that two-word units are implicitly modeled since the phone5-grams modeled in recognition,and4-grams in classification,can straddle word boundaries.The experiments suggest that if transcriptions are available(i.e.the effort to produce them has already been expended),then they can be used to slightly improve performance over the phone-based method(PhonesMM) not requiring transcriptions.For domains A and C,this would give an absolute performance difference of about 2%,while for domain B the difference is around1%.N max Recog.Classif.accuracy accuracy156.670.6259.171.2359.571.5460.073.2562.374.6Table5:Phone recognition accuracy and phone string classification accuracy(PhoneMM with no rejection)for increasing values of N max for domain A.N max Recog.Classif.accuracy accuracy027.969.2138.370.7248.674.7353.377.6455.179.2555.780.8Table6:Phone recognition accuracy and phone string classification accuracy(PhoneMM with no rejection)for increasing values of N max for domain B.Whether it is optimal to train the word-based classifier on the transcriptions(WordsHH)or the output of the recog-nizer(WordsHM)seems to depend on the particular data set.When the operational setting of utterance classifica-tion demands very high confidence,and a high degree of rejection is acceptable(e.g.if sufficient human backup operators are available),then the small advantage of the word-based methods is reduced further to less than1%. This can be seen from the high rejection rate rows of the accuracy tables.Effectiveness of Unsupervised TrainingTables5,6,and7,show the effect of increasing N max (thefinal iteration number in the unsupervised phone recognition model)for domains A,B and C,respectively. The row with N max=0corresponds to the initial un-weighted phone loop recognition.The classification ac-curacies shown in this table are all at0%rejection.Phone recognition accuracy is the standard ASR error rate ac-curacy in terms of the percentage of phone insertions, deletions,and substitutions,determined by aligning the ASR output against reference phone transcriptions pro-duced by the pronounciation component of our speech synthesizer.(Since these reference phone transcriptions are not perfect,the actual phone recognition accuracy is probably slightly higher.)Clearly,for all three domains, unsupervised recognition model training improves bothN max Recog.Classif.accuracy accuracy159.861.8265.364.3368.166.3469.167.4569.368.2Table7:Phone recognition accuracy and phone string classification accuracy(PhoneMM with no rejection)for increasing values of N max for domain C.recognition and classification accuracy compared with a simple phone loop.Unsupervised training of the recogni-tion model is particularly important for domain B where the quality of recordings is not as high as for domains A and C,so the system needs to depend more on the re-estimated n-gram models to achieve thefinal classifica-tion accuracy.5Concluding RemarksIn this paper we have presented an utterance classifica-tion method that does not require manual transcription of training data.The method combines unsupervised re-estimation of phone n-ngram recognition models together with a phone-string classifier.The utterance classifica-tion accuracy of the method is surprisingly close to a more traditional method involving manual transcription of training utterances into word strings and recognition with word trigrams.The measured absolute difference in classification accuracy(with no rejection)between our method and the word-based method was only1%for one test domain and2%for two other test domains.The per-formance difference is even smaller(less than1%)if high rejection thresholds are acceptable.This performance level was achieved despite the large reduction in effort required to develop new applications with the presented utterance classification method.ReferencesH.Alshawi and S.Douglas.2001.Variant transduction: A method for rapid development of interactive spoken interfaces.In Proceedings of the SIGDial Workshop on Discourse and Dialogue,Aalborg,Denmark,Septem-ber.R.Carpenter and J.Chu-Carroll.1998.Natural language call routing:a robust,self-organizing approach.In Proceedings of the International Conference on Speech and Language Processing,Sydney,Australia.J.Choi,D.Hindle,J.Hirschberg,F.Pereira,A.Singhal, and S.Whittaker.1999.Spoken content-based audionavigation(scan).In Proceedings of ICPhS-99(In-ternational Congress of Phonetics Sciences,San Fran-cisco,California,August.J.T.Foote,S.J.Young,G.J.F Jones,and K.Sparck Jones.1997.Unconstrained keyword spotting using phone lattices with application to spoken document puter Speech and Language,11(2):207–224.Y.Freund and R.E.Schapire.1997.A decision-theoretic generalization of on-line learning and an application to boosting.Journal of Computer and System Sciences, 55(1):119–139.A.L.Gorin,G.Riccardi,and J.H.Wright.1997. 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