Original papers
A ?eld survey system for land consolidation based on 3S and speech recognition
technology
Xiaochuang Yao a ,b ,Dehai Zhu a ,b ,Sijing Ye a ,b ,Wenju Yun b ,c ,Nan Zhang a ,b ,Lin Li a ,b ,?
a
College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China
b
Key Laboratory of Agricultural Land Quality,Monitoring and Control,Ministry of Land and Resources,Beijing 100083,China c
Land Consolidation and Rehabilitation Center,Ministry of Land and Resources,Beijing 100035,China
a r t i c l e i n f o Article history:
Received 23October 2015
Received in revised form 1July 2016Accepted 16July 2016
Keywords:3S
Speech recognition Land consolidation Field survey system
a b s t r a c t
The main objective of this study is to develop a ?eld survey system for land consolidation based on 3S (geographic information system,GIS;Global Positioning System,GPS;and remote sensing,RS)and speech recognition technology.Field survey in land consolidation is a complex and high-tech process.Traditional survey methods are dif?cult to use in locating,measuring,recording,and other related tasks.Through 3S and speech recognition technology,Android smart phones could address the aforementioned problems by providing a new method of land information collection.In this study,we present a land con-solidation ?eld survey system (LCFSS),which is developed on an Android mobile platform and integrates 3S and speech recognition technology to support the ?eld survey of land consolidation.The proposed sys-tem is made advantageous by its low cost,high ef?ciency,portability,and user-friendliness.To improve the usability and feasibility of the LCFSS for decision making,we develop a data-adaptive development model,data compression model,three-parameter model for coordinate registration,and speech process-ing model.With the Uni?ed Modeling Language,5functional modules and more than 16application cases are described.On the basis of these models,the functions of system management,data import,pro-ject survey,coordinate registration,and data output are implemented by adopting the system architec-ture with four layers.The key achievement is tested and applied to a land consolidation survey in the provinces of Ningxia,Anhui,Shandong,and others.Results show that the ef?ciency of land information collection and other functions is improved with the use of the proposed system.Therefore,the approaches and methodology presented in this work could serve as a reference for those who are inter-ested in developing mobile system applications based on 3S and speech recognition technology.
ó2016Elsevier B.V.All rights reserved.
1.Introduction
Field survey for land consolidation is signi?cantly dif?cult because of its complex process and high-tech requirements (Jia et al.,2009;Xi et al.,2013).Traditional survey methods necessitate a considerable amount of time and effort and are also dif?cult to use in locating,measuring,and recording tasks (Jia et al.,2009;Wang et al.,2015a ).For example,with a paper map of one land consolidation project,workers tend to get lost because of the large area of the land consolidation project.In such a case,they would need to write down detailed information,such as location,length,and agricultural land type,to collect data about land features.For-tunately,3S technology,as the core of information engineering technology,provides a new method for collecting land information and thereby overcomes the aforementioned issues.For instance,geographic information systems provide technical support for data analysis and expression (Zhang et al.,2014),positioning through the Global Positioning System (GPS)can be used in ?eld investiga-tion systems to improve the accuracy of data acquisition (Doner and Yomralioglu,2008;Mesas-Carrascosa et al.,2012),and remote sensing (RS)provides large-scale multi-source data and support for macro decision making.With the development of smartphones or personal digital assistants (PDAs)and the improvement of hard-ware performance in mobile terminals in recent years,integrated 3S technologies that are useful in spot investigations for land recla-mation project evaluation have been fully realized.In addition,data input methods are crucial in providing working ef?ciency in outdoor environments.However,using the Chinese input method usually requires several letters for one word as input,and in some cases,the variety of answers available makes choosing the right
https://www.doczj.com/doc/13986544.html,/10.1016/https://www.doczj.com/doc/13986544.html,pag.2016.07.0130168-1699/ó2016Elsevier B.V.All rights reserved.
?Corresponding author at:College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China.
E-mail address:lilincau@https://www.doczj.com/doc/13986544.html, (L.Li).
one dif?cult.The development of speech technology has improved the ef?ciency of?eld work(Huang and Chi,2012).With this tech-nology for land consolidation survey,users simply need to provide their voice input through the Chinese input method in their mobile phones;their voice data are then translated into text data auto-matically and quickly(Huyan et al.,2014).
With the development of3S technologies,several types of ?eld survey systems have emerged in many industries,some of which adopt more than one technology.The inability of informa-tion systems based on desktop computers or the web to meet the requirements of real-time and portable data collection in the?eld(Che et al.,2010;Yan et al.,2015)has prompted the development of many?eld survey systems.With the maturity of mobile technologies,such as cellular phones and PDAs,work-ers are now able to collect data and obtain decision support wherever and whenever they want.Through GPS technology, information collection systems are increasingly being used in precision agriculture(Montoya et al.,2013),agricultural land leveling surveys(Li et al.,2005),?eld area measurement,and so on.With GPS and GIS technologies,the application of?eld survey technologies for land consolidation(Wang et al.,2015b) and variable rate irrigation control systems(Bartlett et al., 2015)has undergone obvious development.Moreover,3S tech-nologies have been successfully applied to insects(Han et al.,
its large size(Ye et al.,2014).In the proposed land consolidation ?eld survey system(LCFSS),a data compression method is used to store RS data on mobile devices,thus ensuring the availability of global project data on site.Moreover,speech recognition tech-nology is adopted,and a Chinese word segmentation model is developed to improve the ef?ciency of speech recognition through a local land consolidation word database.
The proposed?eld system for land consolidation based on3S and speech recognition technology is aimed at data acquisition for project-scale land consolidation with high ef?ciency.The pro-posed system bene?ts not only the government through the provi-sion of progress information but also the participating personnel through the monitoring of their location and improvement of their work ef?ciency in the?eld.To ensure that the techniques and models are user-friendly in?eld surveys,we develop the LCFSS with a data-adaptive development model,which equips the system with improved expansibility and portability.
2.Design of LCFSS
2.1.System architecture
The main purpose of the LCFSS is to provide?eld survey equip-
660X.Yao et al./Computers and Electronics in Agriculture127(2016)659–668
(2)Data layer
The second layer is the data layer.The data layer stores and manages different types of data,including vector,raster,and the-matic data.For one land consolidation project,we use a planning map,a status map,remote sensing data,and inconsistent features.
A SQLite database is utilized as the medium between of?ine vec-tors or XML data and data collection work;it holds local land speech words.Raster data are stored in a secure digital(SD)card in a pyramid format.
(3)Inter-medium layer
The third layer is the inter-medium layer.The inter-mediate layer,which consists of a database interface and a mobile GIS developer kit,bridges data application and data storage.In this way,the interaction details between components and operating systems are concealed,and development ef?ciency is thus improved.
(4)Function layer
The fourth layer is the function layer.Through the support of the aforementioned layers,the LCFSS provides functions of map control,data collection,trace tracking measurement diagram, and others.The application layer is constructed on the basis of the inter-mediate layer.As the executor of functions for data queries,editing,and analysis,the function layer supports concrete operations and provides a user interface(UI)for collecting index data.2.2.Data processing
Field survey in land consolidation is a complex and high-tech process.The?rst step in this process is data processing.During dif-ferent periods,the different types of generated data(.JPG n.TIF n. DWG)result in the lack of unity for data types.Such drawback leads to inconvenient data storage and transmission.The work content of investigation is also changing with different stages of one land consolidation project.In the current paper,we transform all data into two data types,namely,.TPK and.SHP,and use XIAN 80(geographic coordinate system,GCS)as the coordinate system (see Table1).These relevant tasks are mainly performed in ArcMap 10.1.
2.3.Requirement model
According to the requirements of the system function,5models with16use cases are diagrammed in the Uni?ed Modeling Lan-guage,which is helpful in understanding operation?ow(Li et al., 2010)and later development.Fig.2shows the case diagram of the LCFSS for users,along with the following?ve models:(1)data import,which involves loading vector and raster data into the sys-tem from a SD card;(2)project survey,in which users can edit and add map features(points denote farm wells,lines denote channels, polygons denote cultivated lands,etc.)through the GPS and GIS technology;(3)coordinate registration,which provides the transfer mathematical model from GPS WGS84coordinates to WGS XIAN80coordinates,to improve the accuracy of the collected spatial data;(4)data output,which involves the export of the collected data from the LCFSS to the PC display;(5)system
Table1
Data requirements.
Data name Data type(before)Data type(after)Coordinate system(before)Coordinate system(after)
LC-planning map.JPG n.TIF n.DWG.TPK None XIAN80(GCS) LC-status map.JPG n.TIF n.DWG.TPK None XIAN80(GCS) LC-completed map.JPG n.TIF n.DWG.TPK None XIAN80(GCS) LC-image map.TIF.TPK None XIAN80(GCS) LC-inconsistent features.SHP.SHP XIAN80(GCS)XIAN80(GCS)
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management,which includes system update,contact information and help document,data clearance,and GPS network set.
3.Implementation of LCFSS
With the development platform Eclipse,we develop the imple-mentation of the LCFSS,which is based on the following hardware and software speci?cations:
Pentium IV2500MHz processor PC with Windows7and Ether-net card.
Intel X Scale312MHz processor PDA with Android Mobile4.0, GPRS,Wi-Fi,and SD interface.
Eclipse4.4.
development model is designed for the proposed system to solve this problem.As shown in Fig.3,all spatial data of one land consol-idation project are divided into three main classes of data,namely, (1)raster,(2)shape?le,and(3)GPS.As a result of the differences in data classes,different data tables are generated automatically. According to the data analysis,methods for organizing and index-ing data can be automatically executed to reduce the in?uence of data type,range,and size.
With the data-adaptive development model,the system could implement dynamic spatial data analysis to ensure that different types of spatial data with different spatial ranges could be identi-?ed,organized,and displayed automatically for?eld data collec-tion.Data processing(Section2.2)is?rst performed prior to the input of data into the system.
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LCFSS because the system works best with maps that do not change frequently,such as planning maps or the completed maps of land consolidation projects.Although creating a cache tile pack-age is time consuming,the cost is only a one-time expense.
3.3.Coordinate registration model
The coordinate system of the location information from the GPS is WGS-84(Gaikwad and Pawar,2014;Lantzos et al.,2013), whereas that from the LCFSS is XIAN80(GCS).Hence,to ensure the accuracy of location data,GPS data must be subjected to coor-dinate system transformation from WGS-84to XIAN80(GCS).The most common transformation methods include seven-,four-,and three-parameter models.Given that the area of the land consolida-tion project is approximately10km,the results of the models at this scale vary only slightly.In this system,the three-parameter model is adopted,and the process is shown in the following steps:
(1)Select one or more pairs of known coordinate points:WGS-
84and XIAN80(GSC).
(2)Select the model formula:the three-parameter model given
by
X
2 63
7
D X
2
6
3
7
x
2
6
3
7
registration model of the LCFSS,we can ensure that the accuracy
of the GPS data is based on the mobile devices and consistent with
the impact of different coordinate systems.
3.4.Speech processing model
The speech processing model in the LCFSS aids workers in col-
lecting basic information on land consolidation projects,such as
land and road types.Fig.4shows that the speech processing model
includes?ve steps,which starts with the voice input of the speaker
and ends with the data storage in the SQLite tables.In this work,
we adopt of?ine speech processing,and thus,before the system
is run,the land key word database is trained with the speech pro-
cessing model.Then,the dataset is matched with speech partici-
ples in the?eld survey process.
We adopt the hidden Markov model toolkit to achieve of?ine
speech recognition from the voice input of speakers.As shown in
Fig.4,a Chinese word segmentation model is implemented with
the maximum matching method to split the speech recognition
results into many single words or new string arrays.Thereafter,a
data processing model translates the new string arrays into Hash-
Map data,in which the key is the data collection?eld(such as land
type and road type)and the value is the collection result(such as
cultivated?eld and?eld road).Finally,the system stores the Hash-
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(2)Data management
The LCFSS is used in the project-scale land consolidation.The dataset in the system mainly includes a planning map,a status map,a completed map,an image map,and inconsistent features (Table1).
Users can easily interact with the contents of the database and run spatial analysis models by clicking buttons to manage data.As shown in Fig.5,the steps for data management using the LCFSS are as follows:
(c)Edit the information on the subject or renew the geographic
elements.
(d)Save the data and move on to the next one.
As illustrated in Fig.7,many miscellaneous functions are devel-oped to improve the operation of the system.These functions include map measurement,spatial orientation,trace tracking, coordinate registration,and so on.
(a)Map measurement
management interfaces of the LCFSS:(1)main interface with?ve function models,(2)data import interface,(3)system map data control 664X.Yao et al./Computers and Electronics in Agriculture127(2016)659–668
(d)Coordinate registration
As detailed in Section3.2,coordinate registration is aimed at promoting the precision of GPS data.
(e)System management
This function involves the system update,net set,data clear-ance,and user assistance.
4.System evaluation
For the system evaluation of the LCFSS,three different types of mobile terminals are tested:PDA,smartphone,and professional GPS devices.This system evaluation test mainly includes three aspects of content,namely,(1)function of the data integration dis-play with the cache tile package of the raster data,(2)location accuracy of the GPS data with the coordinate registration model in this system,and(3)data collection with the speech recognition technology.
Every mobile device maintains a basic storage space of8–16GB or more.All of the data of one land consolidation project require a storage space of not less than7GB and may thus slow down devices.Through the data compression model proposed in this work,the data size is compressed by about?ve times,and the dis-play speed becomes nine times faster than before(see Table2).
To ensure the accuracy of the GPS data,using a professional GPS with a coverage of less than1m in4s is preferable.However,with cost taken into account,PDAs and smartphones are more widely data via a professional GPS is direct,the data accuracy achieved with PDAs is about7.35m,and the data accuracy achieved with smartphones is approximately13.32m.In the same test environ-ment involving the coordinate registration model presented in this paper,the PDA achieves a data accuracy of about4.12m,whereas the smartphone achieves a data accuracy of approximately6.03m. After modi?cation,the GPS data can meet the data accuracy requirement of the given land consolidation project.The users can then choose different Android-based platforms according to their work requirements.
With regard to speech recognition,the main performance parameters include error rate(ER),accuracy rate(AR),and recogni-tion speed.
ER?
ItDtS
N
AR?
NàDàS
N
RS?
R time
S time
e2T
where N includes all the words in the land key word database,I includes the inserted words,D denotes the deleted words,and S represents the replaced words.The recognition time is the speech time as a unit.For example,if speech time is2h and recognition time is6h,then the recognition speed is3ST.
The number of test samples is100,which includes5people with20speeches each.The real dataset comprises4land consoli-dation tables,including14classes and52Chinese words.It includes ditches,roads,farmland,agricultural wells,and other land features.Before the test,all of the real datasets are stored in the SQLite tables and trained with the speech processing model.As the contrast test results show(see Table3),the speech processing model in the LCFSS meets the required application accuracy;that is,an error rate of not more than6%and a recognition speed of
data collection interfaces of the LCFSS:(1)main function model interface,(2)spatial data query interface,(3)spatial editing interface,(4)editing editing interface,(6)polygon collection interface,(7)attribute collection interface,and(8)pictures of collection interface.
In addition to the above system tests,all system functions are tested during use in the provinces of Ningxia,Anhui,Shandong,etc.A case study on the LCFSS is presented in the next section.5.Case study:land consolidation survey in Ningxia,China In this section,a case study on the LCFSS is described on the basis of the factual dataset in Table 4.We take one major land con-solidation project in Ningxia province as an example.The total area is 3363.5ha.The three basic maps are shown in Table 4.On the basis of the data processing in Section 2.2,we obtain inconsistent features,such as ?eld roads,ditches,and newly added cultivated lands.This application case study is aimed at surveying the real progress and verifying the inconsistent features of the land consol-During the course of this investigation,we tested all the func-tions of the LCFSS,as shown in Section 3.5.In the project scale,the LCFSS could meet the requirements well.To ?nish this project survey,we established a survey schedule with the LC-image map and then ensured that all inconsistent objects were within our https://www.doczj.com/doc/13986544.html,ing the GPS orientation function,we arrived at the survey features one by one and edited or renewed the features with spa-tial or attribution properties using the GIS functions.We used the speech input function to enter or select lists containing the data collection information.We took pictures as well.The results for one project are shown in Fig.8.
For the survey results in this application case,146inconsistent features were veri?ed,24new features were collected,and more than 250pictures were obtained from the investigated scene.In Fig.8,0means ‘‘true,”which indicates that the feature really exists,and 1means ‘‘false.”The additional information about the features,such as the attributes and pictures,was assigned with a unique ID Table 2
Contrast test between cache tile package and raster data of one land project.Data type
Data size Display speed Raster data
8.4GB 3.78s Cache tile package
1.61GB
0.4s
Table 3
Contrast test between lab and ?eld results of the speech processing model.Location Error rate (RR),%Recognition speed (RS)Lab 3.7 1.83Field
5.6
1.89
Table 4
Real dataset for major land consolidation project in Ningxia,China.Data name
Data type Size Size (compressed at ?ve levels)LC-planning map .TIF 1.26GB 0.47GB LC-status map .TIF 1.35GB 0.53GB LC-image map .TIF 0.94GB 0.38GB Field road .SHP 64KB /Field ditch
.SHP 56KB /Newly added cultivated land
.SHP
48KB
/
miscellaneous function interfaces of the LCFSS:(1)measurement type selection interface,(2)polygon measurement result interface,(3)spatial spatial navigation,(5)trace tracking interface,(6)and (7)coordinate registration interface,and (8)system management interface.
system and exported in one folder.Applying the LCFSS could improve the ef?ciency of?eld work and ensure the scienti?c accu-racy of data collection.In addition,the LCFSS allows for an easy integration with other systems because of the standardization of the data results.
6.Discussion
The proposed smartphone system is bene?cial for land consol-idation?eld survey at a project scale as it provides accurate loca-tion information and formidable GIS functions.The accurate location information generated with the GPS model provides a spa-tial orientation feature,which enables users to determine their current location and target destination.RS data as the main data serve as the basic map.By comparing the different periods of RS image data,we can master land consolidation projects and their corresponding changes.The different features from the RS data serve as the main investigation objects.GIS technology facilitates land consolidation.Speech recognition technology,as an auxiliary function,makes the data acquisition system convenient and quick.
The system test shows that3S technology and speech recogni-tion signi?cantly improve the quality and ef?ciency of the?eld investigation work for land consolidation projects.The system could address a series of practical problems and make complex scene investigation work highly ef?cient.For example,during pro-ject inspection,investigators can easily determine their position and direction,identify project area boundaries,and locate project construction sites and scope changes.Moreover,users can deter-mine whether the work routine layout is in line with the planning and design and whether the completed construction task should be approved.
7.Conclusion
In this study,an integrated system for the?eld survey of land consolidation projects using Android-based smartphones or PDAs is successfully designed by using ArcGIS API for Android,Eclipse, SQLite,and JAVA programming language.This system provides sys-coordinate registration,data export,and system management.The system graphical UI offers single or double click functionality.The above combination of software indicates that the system functions are ef?cient enough to bring the following remarkable advantages for the LCFSS.First,the proposed system realizes data integration in mobile phones or PDAs.Data format exchange,data interoper-ability,and direct data access provide a data basis for the?eld sur-vey of land consolidation and facilitate the sharing of data between PDA and workstations based on uni?ed standards.Second,the pro-posed system provides a?eld survey system for land consolidation and realizes the integration of multi-source data,spatial query, spatial orientation,and map measurement.Thus,the system allows users to obtain scienti?c information technology support for land consolidation survey work.Third,the technology devel-oped in this study,which is based on3S and speech recognition technology,can be considered as infrastructure for data providers for other related applications.
According to the progress of our project,the system is set to be upgraded with further improvements in online data access,data wireless transmission,and so on.
Acknowledgment
This work was conducted as part of the‘‘Land Management Major Project Dynamic Monitoring Method and Technology Research”,which was sponsored by Ministry of Land and Resources under grant201305410810073.
References
Bartlett,A.C.,Andales,A.A.,Arabi,M.,Bauder,T.A.,2015.A smartphone app to extend use of a cloud-based irrigation scheduling https://www.doczj.com/doc/13986544.html,put.Electron.Agric.
111,127–130.
Ben-Harush,O.,Carroll,J.A.,Marsh,B.,https://www.doczj.com/doc/13986544.html,ing mobile social media and GIS in health and place research.Continuum J.Media Cult.26,715–730.
Che,Y.,Li,M.,Zheng,L.,Deng,X.,2010.Development of a movable farm-data acquisition system with PDA and GPS.Trans.Chin.Soc.Agric.Eng.26,109–114. Doner, F.,Yomralioglu,T.,2008.Examination and comparison of mobile GIS technology for real time geo-data acquisition in the?eld.Surv.Rev.40,221–234.
Gaikwad,P.K.,Pawar,S.J.,2014.Designing and implementation of real-time GPS receiver system for navigation and location based services.Int.J.Adv.Res.
https://www.doczj.com/doc/13986544.html,nd consolidation project survey in Ningxia,China.
Han,Y.,Shan,X.,Zhu,D.,Zhang,X.,Zhang,N.,Zhan,Y.,Li,L.,2011.Design and implementation of locust data collecting system based on android.In:Advances in Computer Science and Education Applications-International Conference.In: Communications in Computer and Information Science,Qingdao,China,pp.
328–337.
Huang,K.L.,Chi,T.S.,2012.TDOA information based VAD for robust speech recognition in directional and diffuse noise?eld.In:20128th International Symposium on Chinese Spoken Language Processing,pp.126–130.
Huyan,Z.,Xu,L.,Fang,S.,Liu,Z.,Zhang,X.,Li,L.,2014.Field information acquisition system research based on of?ine speech recognition.Int.J.Database Theory Appl.7,45–58.
Jia,W.,Liu,J.,Yu,L.,Wang,M.,2009.Development and application of?eld survey technology based GPS and GIS for land consolidation.Trans.Chin.Soc.Agric.
Eng.25,197–201.
Lantzos,T.,Koykoyris,G.,Salampasis,M.,2013.FarmManager:an Android application for the management of small farms.Proc.Technol.8,587–592.
Li,M.,Qian,J.-P.,Yang,X.-T.,Sun,C.-H.,Ji,Z.-T.,2010.A PDA-based record-keeping and decision-support system for traceability in cucumber https://www.doczj.com/doc/13986544.html,put.
Electron.Agric.70,69–77.
Li,Y.,Xu,D.,Li,F.,Bai,M.,Zhang,S.,2005.GPS application in agricultural land levelling survey.Trans.Chin.Soc.Agric.Eng.21,66–70.
Luvisi,A.,Pagano,M.,Bandinelli,R.,Rinaldelli,E.,Gini,B.,Scartòn,M.,Manzoni,G., Triolo,E.,2011.Virtual vineyard for grapevine management purposes:a RFID/ GPS https://www.doczj.com/doc/13986544.html,put.Electron.Agric.75,368–371.
Mesas-Carrascosa,F.J.,Castillejo-Gonzalez,I.L.,de la Orden,M.S.,Garcia-Ferrer,A., 2012.Real-time mobile phone application to support land https://www.doczj.com/doc/13986544.html,put.
Electron.Agric.85,109–111.Montoya,F.G.,Gomez,J.,Cama,A.,Zapata-Sierra,A.,Martinez,F.,De La Cruz,J.L., Manzano-Agugliaro,F.,2013.A monitoring system for intensive agriculture based on mesh networks and the android https://www.doczj.com/doc/13986544.html,put.Electron.Agric.99, 14–20.
Shang,M.,Qin,L.,Wang,F.,Liu,S.,Zhang,X.,https://www.doczj.com/doc/13986544.html,rmation collection system of wheat production risk based on Android smartphone.Trans.Chin.Soc.Agric.
Eng.27,178–182.
Wang,J.,Ge,A.,Hu,Y.,Li,C.,Wang,L.,2015a.A fuzzy intelligent system for land consolidation–a case study in Shunde,China.Solid Earth Discuss.7,1347–1374.
Wang,J.,Yan,S.,Guo,Y.,Li,J.,Sun,G.,2015b.The effects of land consolidation on the ecological connectivity based on ecosystem service value:a case study of Da’an land consolidation project in Jilin province.J.Geog.Sci.25,603–616.
Xi,K.,Yang,X.,Zhao,J.,Han,T.,2013.PDA+3S technology application in land change survey.Geomatics Spatial Inform.Technol.36,91–94.
Yan,J.,Xia, F.,Bao,H.X.H.,2015.Strategic planning framework for land consolidation in China:a top-level design based on SWOT analysis.Habitat Int.48,46–54.
Yang,L.,Hao,L.,Lin,E.,Peng,L.,Li,W.,2012.Intelligent diagnose system of diseases and insect pests in sweet corn based on mobile terminal with Android system.
Trans.Chin.Soc.Agric.Eng.28,163–168.
Ye,S.,Zhu,D.,Yao,X.,Zhang,N.,Fang,S.,Li,L.,2014.Development of a highly ?exible mobile GIS-based system for collecting arable land quality data.IEEE J.
Sel.Top.Appl.Earth Observ.Remote Sens.7,4432–4441.
Zhang,X.H.,Wang,Q.,Wang,H.Q.,Zhang,X.G.,Liu,T.Q.,2014.Fast creating and modifying of land survey polygons using gestures in mobile GIS.In:2014 International Conference on Gis and Resource Management(Icgrm),pp.150–157.
668X.Yao et al./Computers and Electronics in Agriculture127(2016)659–668
浅析语义场理论对英语词汇教学的启发 201010815437 朱友秀指导老师：邱志芳 [摘要]正如英语语法在英语的学习中不可忽视一样，英语词汇教学在英语学习中也起着举足轻重的作用，如果不用方法和技巧，要记住那么多的单词和短语是一件既枯燥又令人头痛的事，而语义场理论为词汇教学提供了系统的理论依据。它用归纳分类和丰富的联想的方法在词与词之间建立起各种各样的联系，使得记忆它们不再那么乏味和单调，本文浅析语义场理论对英语词汇教学的几点启发并以此扩大学生的词汇量，从而提高英语教学与学习的效率，从而实现快乐地学习的目标。 [关键词] 语义场；英语词汇教学；启发 1 引言 词汇是语言的建筑基石和语言意义的载体，它维系着语音和语法。语言若离开了词汇，就无所谓语言。[1]因此词汇学习是英语学习的重要组成部分，掌握词汇的多与少，直接影响学生语言能力的发展与提高。传统的词汇教学没有注意词汇之间的有机联系，学生对词汇的掌握主要靠大量的孤立式强化记忆，而语义场理论认为语言系统中的词汇在语义上是相互联系的，它们共同构成一个完整的词汇系统，为词汇教学提供了系统的理论依据，本文浅析语义场理论对英语词汇教学的几点启发。 1.1 语义场理论 语义场理论（semantic field theory亦称field theory）最早是20世纪20-30年代由德国与瑞士的一些学者提出的。其中最著名的是德国学者特雷尔(J. Trier )。[2]该理论认为：语言系统中的词汇在语义上是相互联系的，它们共同构成一个完整的词汇系统。该理论主要包含三层涵义：其一，语言中的某些词，可以在一个共同的概念的支配下，结合在一起组成一个语义场。[3]例如，由tiger、lion、elephant、bear、dog、cat、pig等词组成animal这个语义场；其二，属于同一语义场的词，不仅在语义上相关，而且在语义上是相互制约、相互规定的。其三，指这个完整的词汇系统是很不稳定的，处于不断变化之中。 1.2 语义场的类型 根据对共同义素的分析角度不同，语义场相应的区分为不同的类型，主要包括：分类义场、上下义场、同义义场、反义义场等。[4] (1)分类语义场。分类语义场是由类义词（因为组成义位的某些义素相同而以类相聚的一群词语）组成的语义聚合体。[5]例如以matter为义素的语义场可以分为solid、liquid、gas等三个分义场，Change 这个义场包括chemical change和physical change，像这样的列子数不胜数。 (2)上下义义场。上下义义场是指一词在上表示总的概念，两个或三个以上的词在下，表示具体概念，在上者称为上义词，在下者称为下义词。上下义义场又分为两元的和多元的。[6]两元的是指一个上义词只包括两个下义词，例如parent这个义场包括father和mother两个词，children这个义场包括son 和daughter。多元的是指一个上义词包括三个或三个以上的下义词，如vehicle这个义场包括car、bus、truck、train等多个词，plant这个义场包括tree, flower, grass, vegetable等。 (3)同义义场。同义义场是指由指称意义相同的义素形成的语义聚合体。在同义义场中，绝对同义词是比较少见的，许多同义词在中心意义上相似的，但其在语体风格、感情色彩、搭配关系上等存在着差别。[7]比如dad和father的语体不同, dad是口语而father是书面语，；再比如pretty girl中的pretty是小巧玲珑的意思，是褒义词而tiny man中的tiny是一种不正常的小的意思，是贬义词，pretty和tiny的感情色彩不同；再比如对……严格，可以有be strict with…与be strict to…两种词组，它们的搭配不同，be strict with sb.,而be strict to sth.。 (4)反义义场。反义义场是由意思相反、相对或矛盾的属于同一词性的和同一范畴的一组词构成的
语义场理论和英语词汇教学 语义学是一门崭新的学科，把语义学用于大学英语教学更是一个全新的内容。英语教学中，很大的一部分内容就是如何把语义学的理论融入到词汇教学当中，使学生能熟练掌握词汇，并能得体地、恰当地运用它们。英国语言学家威尔金斯曾经说过：“没有语法，人们表达的事物寥寥无几，而没有词汇，人们则无法表达任何事物”（Wilkins，1978：111）。由此可见，词汇教学在语言教学中占有重要的地位。目前，我国的大学生英语的学习时间都有5到8年，然而很多学生一谈到英语词汇的学习，都感到头痛。他们普遍存在着下列问题：（1）不能有效巩固已学的单词；（2）不能在特定的语境中恰当地运用单词；（3）错误地使用词的形式，例如：“Be seated, ladies and gentlemen”(formal)，“Have a seat”(informal)，“Take a pew”（colloquial）；（4）不能地道地使用词汇，例如：“no other corner of our planet”；（5）不能有效地把词汇使用在有意义的语境中等。如果能把语义学理论引入英语教学之中，用语义学的原理分析和认识词汇，从而运用更加科学有效的方法提高词汇教学，并从中总结和找出一定的规律，这对提高学生学习英语的兴趣，提高他们掌握英语词汇的能力，进而更好地、恰当地并且得体地使用词汇，都有重要的现实意义。这种理论与实践的结合是很有意义的。 语义学中的语义场理论可帮助学生重温、联想所学词汇，使之变成长期记忆。语义场理论是德国学者J. Tries（伍谦光，1995：94）最先提出来的。根据这一理论，我们知道，尽管语言词汇数目巨大，浩如烟海，但它们并不是杂乱无章的。语义场理论把一种语言的词汇看成是完整的、在语义上相关联的，将一个词与其它词联系起来，而形成语义场。实际上它就是语言中的某些词在一个概念支配下组成一个语义场。例如，在“animal”这个概念下，“cat，dog，horse，tiger，elephant”等单词构成一个语义场，根据词义上的类属关系，看它们是否是上、下义的关系，进而可以推出它们的层次结构。从上面的例句，可以得出从属“animal”这个概念的有“horse，dog，cat and etc.”，每个场下面还可以再分出若干个“子场”，“子场”下面可再分出“次子场”等等，这样就可以使词汇体系及词义系统有次序地展现出来。如果我们了解词与词之间的各种关系，为多个单词设立多种形式的语义场，这样就便于记忆和使用词汇。如表示颜色的语义场有：red，yellow，blue，black，purple，orange等词；还有表示相反意义的语义场如accept/refuse；buy/sell；easy/difficult；true/false等等。通过记忆 laugh（笑）、smile（微笑）、grin（露齿而笑）、giggle（格格地笑、傻笑）、roar（哄笑、大笑）guffaw（捧腹大笑）、mock（嘲笑）、jeer（讥笑）等词，学生不仅弄清了这些词的细微区别，而且学会了正确地使用它们。通过语义场的词汇学习，常常可带出一长串词汇，这样不仅扩大了词汇量，而且不易忘记，所以运用语义场理论学习词汇是扩大词汇量的一种科学有效的好方法。根据德国心理学家H. Ebbinghauss的遗忘曲线学说：复习所需时间比初学所需时间要少得多，复习次数越多，需要时间越少，遗忘速度越慢，因此单词在初学后要马上不断地重复记忆，使之成为长久记忆。同时，运用语义场理论，学生可以对词汇体系进行分析研究，有次序地展现语言的词汇系统。更重要的是，通过语义场，他们能清楚地看到词义之间的相互依存关系和结构层次关系，这样有助于联想和重温所学的词汇。 英语教学的根本目的在于培养学生的语言交际能力 ,因此我们的教学必须把语义摆在一个重要的位置 ,而不能仅仅以语法和结构作为教学的中心。语法结构和意义之间往往存在歧义的问题。结构分析的诸多缺陷可以在意义层次的研究中得到弥补 ,将结构和意义结合起来进行分析和研究的方法对教学产生了深远的指导意义。我们的词汇教学不应该是一味强求词汇量的扩增 ,追求强记效果 ,而是要深入地剖析词汇并把它们联结成一个网络。(Tylor ,1993)如果我们在词汇教学中单纯追求扩大词汇量 ,要求学生死记硬背单词 ,其结
（一）什么是词义 客观事物（这里指人脑以外的所有事物，包括一切生物、非生物、事件以及它们的行动、状态、性质等等）反映在人脑中，产生感觉（sensation），知觉（perception），表象（representation）;人脑把感觉、知觉、表象加以概括和抽象，形成概念（concept）。人们用语言形式把概念固定下来，成为人们交流思想的符号（sign），这就是有一定意义的词。也就是说，词的意义的"人"赋予它的，难怪英国语言学家帕特里奇（Eric Partridge）说过，"Words have no meaning; peope have meaning for them"（词本无义，人赋予之）。传统语义学家通常用三角图形来说明词义，称"词义三角"（triangle of significance）： 意义（概念）Meaning (Concept) 词Word 形式Form……所指对象Referent 这个图形表示：第一，词有两个方向--"形式"和"意义（概念）"。"形式"首先是指词的语音形式，也就是平常所说的发音，其次是指词的书面形式，也就是平常的说的拼写；与此相对的是词的意义（其核心部分是概念），也就是词的内容。每个词都有一定的形式和意义；这两方面缺一不可，统一在每个词中。第二，词义与所指对象联接在一起--一方面，词义在客观世界中是有所指的，另一方面，词义又是客观世界的某一（或某些）事物在语言中的反映。客观世界是无穷无尽、无限丰富的，客观世界的事物之间存在着细微的千差万别。人类语言无法完完全全地准确表达客观世界。一种语言无论词汇多么浩瀚、词义多么丰富，都不足以完完全全地准确反映客观世界。 现代语义学家对"词义三角"提出很多批评，涉及哲学、心理学等各个领域。但是如果我们从学习语言的实用目的出发，粗浅地分析词义、解释有关词义的种种现象，传统语义学提出的"词义三角"还是能说明一些问题的。 （三）词义分析和语义场 前面已经提到，词义是词的内容，每个词有一个或几个意义，每个词义又可以进一步分析成若干个语义成分（semantic compo-nents）或语义特征（semantic features）作为区别性特征（distinctive features）。叶姆斯列夫（Hjelmslev）在本世纪四十年代出版的《语言理论导论》中应用于语义成分分析了"公羊、母羊、男人、女人、男孩、女孩、公马、母马"这组词。至于语义成分分析法（componential analysis）则是美国的人类学家威廉·古迪纳夫（W. H. Doodenough）于1956年提出来的。此后，美国语言学家奈达（Nida）、卡兹（Katz）和福德（Fodor）等人进一步发展了这种方法。举个最简单的例子：man, woman, boy, girl都属于"人"（human）这个语义范围（即语义场，semantic field），以"人"（human）这一共同的语义成分为核心，以男性（male）女性（female），成年（adult 每个词的语义又可以分别通过区别性特征表示为： man: +人+ 成年+ 男性 woman: +人+ 成年-男性 boy: +人- 成年+ 男性 girl: +人- 成年- 男性 把每个词义分析成若干语义成分可以帮助我们比较完整地了解词义，以及词与词之间的关系。例如：adult和grown-up这一对同义词就可以表示为：+ 人+成年，另外再表明它们的文体区别，前者是正式用语，后者是非正式用语。又如man这个词的多义性可以表示为：它有两个词义，第一个词义是+ 人+ 成年+ 男性，第二个词义是+ 人。 词义研究的另一种理论是所谓的"语义场"（semantic field），这个理论最早是由德语言学家特里尔（Jost Trier）在本世纪三十年代初提出来的。他认为，每个词都身居其亲属概念之间，这些词相互之间以及它们特指的那个词一起构成了一个自成系统的整体，这种结构可称为"词场"（das Wortfeld）或语言符号场（das Spraches Zeichenfeld）。其实，语义场就是同一词类的词由于它们之间紧密的联系而形成的一个词汇小体系，这些词具有它们的共有语义成分，体现了它们的概念核心。属于同一个语义场的词除了具有共同的语义成分以外，还具有各种非共同语义成分作为区别性特征。按照区别性特征的不同，语义场可以分为同义、近义类义、反义等几种。同义语义场里的词的概念意义相同，关联意义有差别；近义语义场里的词的共同语义成分的含义在程度上有细微的差别；类义语义场里的词在非共同语义成分的种别上有差异；反义语义场里的词的非共同语义成分的含义截然相反或者相对。各个语义场之间也呈现着包含、并列、部分覆盖等错综复杂的关系。用语义场的概念
关于“笑”的动词语义场分析 12092班杨乐1209114072
一、摘要 语义场理论日益受到语言学家的重视，语义场理论也发展得越来越完善。语义场理论传入我国大陆后，我们运用此理论对汉语义位系统的研究也开始了。本文运用义素分析法，对关于常见的“笑”的动词语义场进行分析，从几个最小语义场入手，对动词进行深入探究。 二、关键词 义素分析法、语义场、动词、笑、义位 三、引言 1、语义场理论的简介 （1）语义场的定义 语义场是指义位形成的系统。如果若干个义位含有相同的表彼此共性的义素和相应的表彼此差异的义素，因而连结在一起，互相规定、互相制约、互相作用，那么这些义位就构成一个语义场。语义场可分为分类义场、部分义场、顺序义场、关系义场、反义义场、两极义场、部分否定义场、同义义场、枝干义场和描绘义场十种类型。从现代语义学的观点来看，一组同义词（不包括等义词）或一组反义词的义位以及一组意义上紧密联系的义位，构成一个最简单的义位系统，是一个最小的子语义场。 （2）语义场的兴起与发展演变趋势 洪堡特是普通语言学的奠基人，他初步具有语义场的概念。最早
提出语义场的概念并进行了认真研究的，是一些德国和瑞士的结构主义语言学家，其中最出名的是特里尔。特里尔的语义场理论是20世纪30年代提出来的。乌尔曼认为特里尔的理论在语义学的历史上开辟了一个新阶段。这一理论后来由他的学生和威斯皆伯进一步发展了。威斯皆伯在30年代曾与特里尔合作，第二次世界大战以后他又继续钻研语义场的理论。结构主义语义学家正确的指出语义场的理论是他们的主要成就。但是在三四十年代，语义场理论的影响是很有限的。到了50年代，乔姆斯基提出了转换生成语法，美国人类语言学家提出义素分析法，语义研究日益受到重视。语义场的理论才引起普遍的注意。当然，50年代以后，人们研究语义场的理论较之三四十年代已有相当的发展了。语义场的理论传入我国大陆后，我们运用这一新理论对汉语义位系统的研究也开始了。语义场可以进一步分作词汇场和联想场两类。 2、本文研究的研究内容 本文运用义素分析法，对关于“笑”的动词语义场进行分析，在表达的感情、声音的不同、嘴角上扬程度（表达感情的激烈程度）、语言类笑容四个不同角度列出最小语义子场，分析常见的关于“笑”的动词的意义。
从语义场理论视角看中西方颜色词意义异同 摘要:特里尔提出的语义场理论对分析词义有重要影响。颜色词语义场中各成分具有共同语义特征,但人在此基础上对颜色产生的感觉联想会引起感情变化,使颜色具有感情价值,从而传递出丰富的文化涵义,于是就出现了各颜色在中西方文化中相互区别的象征意义。语义场理论既有助于我们掌握语义场跟具体词义的关系,同时也可以让我们在中西方文化的对比中更好地掌握各颜色丰富的象征意义。 关键词:语义场理论;语义场类型;颜色语义场;象征意义 中图分类号:H0-0文献标识码:A 文章编号:1003—0751(2009)06—0241—03 一 德国学者特里尔(Trier)首先提出词汇相互间关系构造的理论,即语义场理论。他指出,语义场是单个词和整个词汇之间的现实存在。作为整体的一部分,它们具有与词相同的特征,即可以在语言结构中被组合,同时还具有词汇系统的性质,即由更小的单位组成。 特里尔的语义场理论主要是针对词汇之间的聚合关系的。根据这个理论,词可以在一个共同的语义概念的支配下,相互集结在一起形成一个语义场。例如,色彩词和家族亲属词就是各自处于某种语义场的词汇,支配语义场的共同概念往往是个语义特征。 所以语义场是指在词义上具有某种关联的词集合在一起并且互相规定、互相制约、互相作用而形成的一个聚合体。这种聚合体的主要特征是:聚合体中的各个词都具有共同意义特征,同时又具有区别意义特征。共同意义特征使得不同的字能够聚合在一起,区别意义特征使得不同的词能够相互区别。 语义场理论认为,一种语言词汇中的词在语义上是互相联系的,这些词共同构成一个完整的词汇系统,并且这个词汇系统是不断变化的。这就表明了一个词的词义只有在词作为某个整体中的一个部分时才能显示出来,词只有在词义场中才有意义。① 客观世界万事万物的联系是系统的,词语的语义场系统就是对外部世界的系统编码,它组成了语言的总语义场。语言总语义场是由各子语义场构成的开放系统,这种体系由两种关系构成,即垂直方向的上下义关系(纵聚类关系)和水平方向的相互区别关系(横组合关系)。聚类关系和组合关系是组成语言系统的一个纲,是我们观察、分析、归纳错综复杂的语言现象的一把总钥匙。要分析语义系统的结构关系,必须先确定其结构成分。我们把组成语义系统的基本结构成分称为“义位”。在现代汉语中,义位与义位之间的关系形成了很多类型的语义场。其常见种类有: 1.类属义场 其词义所表达的义位之间有一个种类属与分类的关系。类属义场的成员同属于一个较大的类,比如“杨树、榆树、椿树、橡树”同属树木类,“红色、白色、黑色、黄色、绿色”同属颜色类。典型的还有“亲属场”、“金属场”、“家具场”等都是类属义场。 2.序列义场 序列义场是一种局部的词义现象。它向我们展示的是词义之间的次序和级差现象。如“春、夏、秋、冬”和“优、良、中、差”等。根据其意义类型,序列义场还可以进一步分为时间序列、空间序列、数量序列和等级序列等。 3.关系义场 关系义场一般由两个成员组成,二者处于某种关系的两端,互相对立、互相依靠。如:“老师、学生”便是因教育关系形成的语义场。
[论文关键词]语义场义素分析价值[论文摘要]“语义场理论”是现代语义学中十分重要的理论之一。语义场具有其特有的性质和一定的研究价值。而从语言学角度可以说义素分析法是一种确定语义场和词语义位关系的比较准确可靠的方法。本文将对义素分析及语义场的性质和价值进行初步探讨。“语义场理论”是现代语义学中十分重要的理论之一。20世纪30年代，最早由德国学者特雷尔提出应用于语义学中。语义场作为具有某种共同或者相近语义的语言单位构成的一个集具有其特有的性质和一定的研究价值。而从语言学角度可以说义素分析法是一种确定语义场和词语义位关系的比较准确可靠的方法。一、义素分析义素分析法源于布拉格学派的音位学。布拉格学派认为音位是语音切分的基本单位，即最小的声音意义载体。音位的对立关系是音位学理论中的基本概念。音位对立体现的是两种声音的区别特征。音位学理论后来被美国人类语言学家运用到词语的意义分析中提出了义素分析法。法国结构语义学创始人之一格雷马斯将义素分析法运用于话语的语义分析，此后，义素分析被语言学界普遍接受，并且将其运用到语言及言语的语义研究中。与音位可以分解为区别性特征一样，语义也可分解为区别性特征。一个意义分解成的最小的语义特征就是义素。义素是语义的微观层次，在语言体系中和在言语中直接观察不到。义素的组合才是现实的一项语义，词典学中叫义项。人在说话时能以不同的方式表达同一个思想，听话时能理解不同话语的相同语义。一个初学外语的人，往往竭力逐词再现他听到的话，忘记了一个词，便难以表达思想。所以，一个人如果真正掌握了一种语言就能用自己的话复述思想。这就意味着他在心里已把语义分解为义素，然后把又把义素组合成语义，并组成表达同一思想的不同话语。平常说的“换句话说”就是这种现象。总之，义素分析法将词语义位分解为最小语义单位，可以正确地将具有共同语义成分的词语置入同一个语义场，分析词语义位之间的关系；能够准确地区分词语的意义并在言语活动中选择恰当的词语，从而完成有效交际。因此，从语言学角度可以说义素分析法是一种确定语义场和词语义位关系的比较准确可靠的方法。二、语义场理论“语义场理论”是现代语义学中十分重要的理论之一。语义场理论属于结构主义语言学理论，持客观主义语言哲学观。“场”原是物理原术语，是物质存在的一种基本状态。实物之间的相互作用依靠有关的场来实现。“场”理论研究的是事物或现象之间的相互关系，有某种关系的事物或现象必然或可能聚集在同一个“场”内。传统语义学关于词义的“聚合关系”和“组合关系”研究成果为“语义场”理论奠定了基础。20世纪30年代，“语义场理论”是由德国学者特雷尔最先提出的。特雷尔认为，在一个语义场的范围内，各个词之间是相互联系的，每个词的意义取决于这个语义场内与之相邻的诸词的意义。语言是一个由多个系统组成的多平面、多层级的独立的体系。其中词汇系统中的词语在语义上互相联系、互相依存。词语的意义不是孤零零地存在于词汇系统中，而是在这种相互依存的关系中得以显现和确定。“意义就是指号之间的一种关系，被定义者和定义者之间的一种关系”（沙夫，1979:247）。因此表示同一个或者同一类概念的词语的义位形成一个集合，即一个语义场。（一）语义场具有的性质 1．语义场内语义的联系性语义场内每个词语之间都相互依存并能相互解释。在汉语亲属场中“哥哥”与“弟弟”相对，俄语中“брат”（兄弟）则与“сестра”（姐妹）相对。汉语中用“姐姐”、“妹妹”来补充，它不仅区分男女，而且分出长、幼，而俄语中只区分男、女。在一个语义
西安翻译学院 XI’AN FANYI UNIVERSITY 题 目：论语义场 学生姓名：吕林永 指导教师：林允富 学科专业：对外汉语 2013年 6 月
论语义场 ——浅析语义场在对外汉语教学中的作用 作者：吕林永人文艺术学院 1124110102 摘要：语义场是语义的类聚，是指在词义上具有某种关联的词集合在一起并且相互规定、 相互制约、相互作用而形成的一个聚合体。我们可以通过划分语义场来了解词汇的义素的 异同。所以对于对外汉语的词汇教学而言，只要合理运用划分语义场的方法，对词汇进行 分类，系统性地给汉语学习者进行教学，那么就能在对外汉语教学上达到事半功倍的效果。 关键词：语义场对外汉语词汇教学 一、关于语义场 汉语作为一种语言，具有一切语言共同的属性。从语言的结构上来说，语音是语言的物质外壳，语法是语言的结构，词汇是语言的建筑材料，同时也是语音、语义和语法的载体。因此如果没有词汇当砖做瓦，那么即使掌握了语音和语法，也盖不起语言的高楼大厦。所以在对外汉语教学中，应当把词汇教学作为教学内容的重中之重。 但随着社会的发展演变和人们实践领域的不断扩展，汉语词汇也在不断发展。新词的产生、旧词的复出、词义的演变，使得汉语词汇数量极其庞大，光是《现代汉语常用词表(草案)》就收录了56008个现当代社会生活中比较稳定的、使用频率较高的汉语普通话常用词语①。在这数量庞大的汉语词汇中，还有不少是同音词、同义词。如果教师对词汇教学没有进行系统性规划的话，势必会造成汉语学习者在理解、使用汉语词汇上有所偏差，影响学习者汉语水平的提高。 陈枫在《对外汉语教学法》中提出了词汇教学的四个原则：系统性原则，阶段性原则，交际性原则，文化性原则。其中的系统性原则即指在汉语词汇教学中，必须注意到各个单词在各种系统内的关系。这种关系根据语义场理论表现为聚合关系和组合关系②。聚合关系是在语言系统中各个语义成分在对立的基础上形成的关系，例如：同义、反义、同音、上下义等。因此我们可以用语义场模型及词汇的聚合关系来对汉语词汇进行系统分类，以便在教学中让汉语学习者更好地理解词义，正确使用。 “语义场”这一术语最早是由德国学者伊普森（G. Ipsen）于1924年提出来的。而“语义场”的概念进入中国，则是由北京大学贾彦德教授在《汉语语义学》（1992年）一书中，才系统地提出了汉语的语义场理论③。 “语义场”在《现代汉语》（增订五版）中的解释为：语义场是语义的类聚，既有共同义素又有区别义素的一组词的相关语义聚合为一个语义场④。“场”原是物理学术语，如电场、磁场、引力场等。物理场即相互作用场，是物质存在的基本形态之一。那么语义场则可理解为是对比不同词，辨析划分它们词义之间的共同特点或关系，来组合成一个相互联系、相互对比的概念模型。同一语义场内的各词义都具有共同的义素，同时也有区别的义素，这样便可清晰明了地解释语
收稿日期：2011-01-19 作者简介：王毅力（1980-），男，江西湖口人，广州大学人文学院讲师，中山大学文学博士。研究方向：汉语史。 广东技术师范学院学报（社会科学） 2011年第2期Journal of Guangdong Polytechnic Normal University No ．2，2011 二十年来古汉语语义场研究述评 王毅力 （广州大学，广东广州510006） 摘 要：二十年来古汉语语义场研究取得了一些有价值的成果。本文对古汉语语义场研究成果进行总结评述，以期为 进一步探讨和研究古汉语语义场奠定基础。 关键词：古代汉语；语义场；词汇系统中图分类号：H 13 文献标识码：A 文章编号：1672-402X （2011）02-0062-03 “语义场”(semanticfield)理论是西方现代语义学核心理论之一。在20世纪30年代，德国语言学家特里尔(J. Trier)提出了“语义场”理论。“场”原是物理学术语，语言学家把“场”从物理学借用过来，形成“语义场”的概念，用来指一组意义相关的词的集合。语义场理论的实质，主要是反对那种孤立的、只注重单个词发展的、原子主义式的研究，而强调把词汇和词义作为一个系统来研究。尽管语义场理论遭到许多批评和质疑，但它的提出和实践，为词汇语义学研究开辟了一个新天地。上世纪80年代初，国内学者才将语义场理论引入现代汉语词汇研究当中，运用语义场理论研究古汉语词汇则是更晚的事情。本文在全面占有资料的基础上，分21世纪以前和以后两个时期来总结古汉语语义场的研究成果，以期为进一步研究打下基础。 一、21世纪以前的古汉语语义场研究 王力(1958)在研究汉语“同源词”时指出：“一种语言的语音的系统性和语法的系统性都是容易体会到的，唯有词汇的系统性往往被人们忽略了，以为词汇里面一个个的词好像是一盘散沙。其实词与词之间是密切联系着的。”可见王先生在研究古代汉语词汇时具有了语义场意识。 自觉运用语义场理论对古代汉语词汇系统进行研究，是从上世纪80年代末才开始的。蒋绍愚是较早将语义场理论引入古汉语词汇研究的学者之一。蒋先生(1989)在他的《古汉语词汇纲要》中专辟一节来谈“词在语义场的作用”。他认为“词不是孤立地存在的，它们处在相互的联系之中。一批有关联的词，组成一个语义场。在语言的历史发展中，词在语义场中的分布会产生种种变化。”他将词在语义场的关系分为聚合和组合两种，并举例分析 汉语中两种语义场的发展演变。他明确指出，古汉语语义场研究应该是取几个不同的历史平面(如春秋战国、东汉、魏晋、晚唐五代、南宋、明代等等)，对各个平面上的某个语义场中作比较全面的统计分析，然后再把各个历史平面加以比较，从而观察分析各个语义场在汉语历史演变中的变化。“如果能把数十个或数百个重要的语义场作这样的历史比较，我们对汉语词汇系统的历史演变就会有比较清楚的了解。”蒋先生这种垦荒式的探索，为古汉语语义场研究指明了方向。 解海江、张志毅(1994)在《汉语面部语义场历史演变———兼论汉语词汇史方法论的转折》一文，对语义场理论在汉语词汇史研究中的运用方面有所创新。作者通过详细描写面部母场及其四个子场“额”、“颊”、“腮”、“颏”的历史演变过程，发现了面部语义场发展演变的一些规律。该文在研究方法论上也进行了总结：(1)由分类历时综述转为语义场模式剖析；(2)由开放、分散、原子式转为封闭、系统论；(3)由定性分析转为定性定量相结合分析。该文的出炉，为古汉语词汇语义场研究提供了很好的范例。 吕东兰(1998)的《从<史记><金瓶梅>等看汉语“观看”语义场的历史演变》选择各历史时期的有代表性的文献，分别描写其中的“观看”语义场，再前后加以比较，观察“观看”语义场在汉语中的历史演变。 贾彦德(1999：402)指出：“训诂学、传统语义学研究字义、词义的演变，通常只着眼于个别字、词意义的改变，其实义位的演变常常与系统的变化相联系。”又说：“义位总是处在一定的语义场中，并和同一语义场特别是同一最小子场的其他义位互相联系、互相制约。这样，义位的演变常常互相影响，涉及一个最小子场甚至更大的范围，大量的事实说明了这一点。”贾氏从原有最小子场的消失、原有最小子场的演变、新的最小子场的出现和语义场大