A metrical model of rhythm and intonation for French text-to-speech synthesis
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A METRICAL MODEL OF RHYTHM AND INTONATIONFOR FRENCH TEXT-TO-SPEECH SYNTHESISAlbert Di Cristo, Philippe Di Cristo, Jean VéronisLaboratoire Parole et Langage,Université de Provence & CNRS29 Av. Robert Schuman, 13621 Aix-en-Provence Cedex 1, FranceTel. : +33 4 42 95 36 19, Fax : +33 4 42 59 50 96, E-mail: Albert.DiCristo@lpl.univ-aix.frABSTRACTThis paper presents the prosodic component of a French text-to-speech synthesis system based on a metrical model of rhythm and intonation in which the prosodic well-formedness of utterances is governed by a set of rhythmic and morphosyntactic constraints. We first set out the theoretic basis of the generation of prosodic levels that correspond to the metrical and tonal structure of utterances. Then, we outline the implementation in our system, and, in particular, the prosodic module that produces a metrical interpretation of phrase-level parsed text, by computing relative prominence levels and gen-erating the F0 patterns and segmental duration. This approach produces high quality results for text-to-speech synthesis at a very minimal implementation cost, and enables a realistic modelling of the prosodic vari-ability observed in real speech.1.INTRODUCTIONWe have undertaken a modular research program on the metrical, morpho-syntactic and semantico-pragmatic constraints which govern the prosodic structuring of utterances in French and account for rhythm and intona-tion well-formedness. The first stage of this research program results in the design and implementation of a metrical component for the generation of prosody in a French text-to-speech (TTS) synthesis system.Our approach is motivated by three considerations:•Natural language processing (NLP) techniques do not at present allow robust in-depth syntactic parsing and analysis of the informational organisation of ut-terances.•There seems to exist a general consensus that metri-cal organisation is a prerequisite to the generation of intonation, thus justifying the prominence-based ap-proach ([18][10]).•It is desirable to optimise development efforts and produce high quality synthesis at a minimal cost of implementation.2.THEORETICAL BACKGROUNDIn our approach, the generation of prosody (rhythm and intonation) uses a metrical procedure based on the com-bination of phonological principles and parameters considered as universals, and principles and rules spe-cific to French ([12][6][3]). The formalism adopted is that of the bracketed grid establishing a rigid link be-tween the projection of prominent syllables (or heads) and metrical constituency ([9][14]). Following this the-ory, and in the light of our application, it is crucial to first define the accentable elements which can be pro-jected from the information extracted from the text as well as the different levels of bracketing which can be associated with accentual projections.To this end, the construction of simplified grids which we use to generate French prosody in this first stage of the model is mainly based on an accentual bi-polarisation principle (ABP) [5] which assigns an initial and a final stress to content words and phrases. It must be noted that the word-initial, or secondary, stress has very often not been taken into account in the literature on French prosody, or has been treated as an emphatic accent. This ABP seems to account for most French accentual strategies. It also accounts for the "accentual bridges" (arcs accentuels) whose frequent use has been noted in different speech styles [8], as well as various types of focalisation, both narrow and wide [5].The ABP is part of a prosodic parsing strategy which includes the following four basic rules:(R1)division of the utterance into Intonation Units (IUs);(R2)assignment of a prominence to the right edge of each IU;(R3)assignment of prominence to the left and the right edge of each accentuable word;(R4)reorganisation of prominences to take into account their relative proximity [11].The construction of the metrical grid also makes use of a dominance principle (stress subordination) which iteratively assigns a higher level of prominence to a final stress than to an initial stress, the highest level being assigned to the nuclear stress. This hierarchical strategyaccounts for the prominence relationships at the word level and beyond [6].The mapping on an underlying level between the metri-cal structure and the tonal organisation (Figure 1) is obtained by assigning specific tonal templates to the different metrical constituents which are generated from the prominence projection rules and bracketing. The sequences LL and LH are assigned respectively to ter-minal and non-terminal IUs, while the sequence LH is assigned to internal accent groups—assimilated to Tonal Units (TU), i.e. minimal synchronisation units of the metrical and tonal organisation of the text. This results in a non-linear prosodic structure which is submitted to linearisation constraints that project the tonal segments onto a single tonal tier that can be seen as a surface phonological representation of the text intonation. This linear representation derives from the application of a certain number of principles and rules, in particular a downstep rule which can be applied either locally or iteratively. The representation is encoded by means of the INTSINT prosodic alphabet [12], symbols of which are either absolute: M(id), T(op), B(ottom) or relative: L(ower), H(igher), S(ame), U(pstepped), D(ownstepped) (see also [2] in this volume).The temporal representation is based on data presented in [4] [1]. It uses a quantification of segmental durations into four categories which are associated with the tonal structure of the utterance. The categories are: Normal (y); Lengthened (+), that applies to the segments of the rime in final syllables of minor groups delimited by a final primary stress; Extra-Lengthened (++), that applies to the segments of the rime in final syllables of major groups (IU) delimited by a nuclear accent; Reduced (-), that applies to segmental units included in an accentual bridge, simulating the acceleration of tempo which gen-erally accompanies this type of grouping.3.IMPLEMENTATION3.1NLP ModuleThe NLP module takes raw text as input, and performs tokenisation, sentence recognition, part-of-speech as-signment, grapheme-to-phoneme conversion and phrases-level parsing. These procedures have for the most part been developed in the MULTEXT project [20]. We will not describe in great detail the first stages of processing, since they are very similar to what can be found in other systems.The NLP module uses only a very rough phrase-level analysis of the text, and does not perform deep syntactic analysis. It has been shown by various authors that a complete syntactic parsing of sentences was not neces-sary for producing acceptable prosody ([16][17]). It is in fact likely that human speakers do not have at their disposal a complete parse of long sentences when they read a text, and it is commonly accepted that prosody is organised in prosodic groups (also called prosodic do-mains) constituted by short, phrase-level segments of the text. Many studies have used phrase-level word groupings, usually based on simple and robust heuris-tics. However, it seems important for the sake of natu-ralness that the word grouping heuristics not be deter-ministic, in order to reflect the great amount of variation observed among readers of the same text, and even for the same reader in different portions of the text.The first step of our phrase-level module partitions sentences on the basis of punctuation (commas, dashes, colons, etc.), defining thus the IUs of utterances. Exam-ple:Cette théorie de la littérature, elle avait confirmé ses intuitions.Ö[ Cette théorie de la littérature ][ elle avait confirmé ses intuitions ]Words are then grouped very roughly using a French variant of the chink’n chunk algorithm proposed by [15]. In this algorithm, words are sorted into two cate-gories: the chinks and chunks. Chinks are words that are likely to start a new prosodic group (determiners, verbs, conjunctions, prepositions, etc.). Chunks are categories that are less likely to start a prosodic group (nouns, adjectives, participles, adverbs, etc.). Groups are then determined according to the following regular expres-sion:group = chink* chunk*Example:[ Cette théorie de la littérature]Ö(Cette théorie)(de la littérature)However, this crude strategy produces groups that are sometimes very small and sometimes very long. In ad-dition, it does not have the non-deterministic property mentioned above. Therefore we use two additional steps that can be triggered or not, thus producing a wide range of plausible groupings.Some short groups (e.g. starting with a preposition) can then be merged with the preceding group. Example: (Cette théorie) (de la littérature)Ö(Cette théorie de la littérature)Conversely, long groups can be split (e.g. after the last verb, before the last preposition, etc.). Example:(et même avant cette nouvelle théorie)Ö(et même)(avant cette nouvelle théorie)3.2Prosodic ModuleTonal ImplementationTwo UTs are assigned to each group of words obtained by the NLP module: the first UT is assigned to the first syllable of the first accentable word while the second UT is set on the last syllable of the last accentable word. The surface realisation of this operation consists in five steps:(i)An H tone is assigned to the initial and final ac-cents, then intermediate L tones are aligned and adjusted.(ii) A T and a B tone are assigned respectively to the final syllable of non-terminal and terminal IUs(iii) A D tone is set on the final syllable of a sequence of words delimited by ":", and also on the penulti-mate syllable of terminal and non-terminal IUs.(iv)Initial accents are suppressed if they are immedi-ately preceded by a final accent.(v)While there is no specific declination component in this model, a sequence of HLH tones automati-cally introduces an iterative lowering of the second H.Duration implementationSyllables and phonemes duration are generated in rela-tion with the tones, computed as follows:(++)lengthening by k2 (k2>k1), for all IU-final D, T and B tones(+)lengthening by k1 (k1>1.0), for all word final H tones(-)shortening by k3 (k3<1.0), for all sements between two H tones on an accentual bridge(y)mean reference duration of the phoneme, for all other segments.F0 curve generationAn F0 curve modelled as a quadratic spline is then gen-erated from a set of targets points derived from the lin-ear sequence of INTSINT symbols (Figure 2). The target values are defined using a mean value m (for the target M) corresponding to the speaker's reference level. Absolute targets T and B are fixed relatively to M tak-ing into account perceptual data [19] and statistical analysis [20]. Relative points are computed by linear regression with respect to the preceding target.4.CONCLUSIONThe strict application of rules R1-R4 in §2 above gener-ates an over-specified prosody representing a certain style of hyper-speech characteristic of reading and lec-turing. The flexibility of the model makes it possible to adopt other strategies of metrical coding in particularly through rule R4 by taking into account a temporary or general inhibition of initial prominences (more conser-vative style) and of some final prominences within a group of words (realisation of accentual bridges). The introduction of this variability which accounts for the probabilistic character of accentuation in French is in our opinion a major advantage to improve the natural-ness of speech synthesis.This approach appears particularly efficient in speech synthesis from text in that it allows a significant im-provement of quality without needing a deep analysis of the textual form which is impossible to obtain from state of the art techniques and NLP.5.ACKNOWLEDGMENTSWe grateful to Thierry Dutoit for the MBROLA synthe-siser [7], Daniel Hirst for his useful comments and Rob-ert Espesser for the signal editing software used in this study.6.REFERENCES[1]Astesano, C., Di Cristo, A., Hirst, D. (1995). Dis-course-based empirical evidence for a multi-class stress system in French, Proc. XIIth I.C.Ph.S., 630-633.[2]Campione, E., Flachaire, E., Hirst, D., Véronis, J.(1997). Stylisation and symbolic coding of F: A quantitative model (in this volume).[3]Di Cristo, A. & Hirst, D.J. (in press). L'accentua-tion non-emphatique en français: stratégies et paramètres, in Polyphonie à Fónagy, Paris: L'Har-mattan.[4]Di Cristo, A. (1985). De la Microprosodie à l'Into-nosyntaxe, Thèse d'Etat, Université de provence. [5]Di Cristo, A. (forthcoming). Vers une modélisationde l'accentuation du français, Travaux de l’Institut de Phonétique d’Aix, 17.[6]Di Cristo, A., Hirst, D. (1993). Rythme syllabique,rythme mélodique et représentation hiérarchique de la prosodie du français, Travaux de l’Institut de Phonétique d’Aix, 15, 9-24.[7]Dutoit, T., Leich, H. (1993). MBR-PSOLA : Text-to-speech synthesis based on an MBE re-synthesis of the segments database, Speech Communication, 13, 435-440.[8]Fónagy, I. (1980). L'accent en français: accentprobabilitaire, In Fónagy, I., Léon, P.R. (Eds), L'Accent en Français Contemporain, Paris: Didier, 123-233.[9]Halle, M., Vergnaud, J.R. (1987). An Essay onStress, Cambridge: MIT Press.[10] Heuft, B., Portele, T. (1996). Synthesizing prosody:a prominence-based approach, Proc. ICSLP’96,Philadelphia. 1361-1364.[11] Hirst, D., Di Cristo, A., Espesser, R. (forthcoming).Levels of representation and levels of analysis for the description of intonation systems. In Horne, M.(Ed.), Prosody: Theory and Experiment, Dordrecht:Kluwer Academic Publishers.[12] Hirst, D.J. & Di Cristo, A. (1984). French intona-tion: a parametric approach, Die Neueren Spra-chen, 83 (5), 564-569.[13] Hirst,D., Di Cristo, A. (in press) A survey of into-nation systems. In Hirst, D., Di Cristo, A. (eds) In-tonation Systems : a Survey of Twenty Languages .Cambridge University Press, 1-44.[14] Idsardi, W.J. (1992). The Computation of Prosody,PhD Dissertation, MIT.[15] Liberman, M., Church, K. (1992). Text analysisand word pronunciation in text-to-speech synthesis.In Furui, S., Sondhi, M.M. (Eds), AdvancesinSpeech Signal Processing, New York: Dekker,791-831.[16] Monaghan, A. I. C. (1900). A multi-phrase parsingstrategy for unrestricted text, Proceedings of the ESCA Tutorial Day on Speech Synthesis, Autrans (France), 109-112.[17] O’Shaughnessy, D. (1990). Relationships betweensyntax and prosody for speech synthesis. Proceed-ings of the ESCA Tutorial Day on Speech Synthe-sis, Autrans (France), 39-42.[18] Pierrehumbert, J. (1981). Synthesizing intonation,JASA, 70 (4), 985-995.[19] Rossi & Chafcouloff (1972). Les niveaux intona-tifs, Travaux de l’Institut de Phonétique d’Aix, 1,167-176.[20] Véronis, J., Hirst, D., Espesser, R., Ide, N. (1994).NL and speech in the MULTEXT project. AAAI'94Workshop on Integration of Natural Language and Speech, Seattle, 72-78.Text analysis Cette thé orie de la littérature , elle avait confirmé ses intuitions . IUs [ ] [ ]Word groups ( ) ( ) ( ) ( ) Cette thé orie de la littérature , elle avait confirmé ses intuitions . * *)* *) * * *) * * *) * * * *) * *) * *) * *) | | | | | | | | Metrical * *) * *) * *) * *) grid | | | | * *) * *) | | * *) | *Tonal PlaneCette thé orie de la littérature , elle avait confirmé ses intuitions . Underlying L[ ( ) ( ) ( ) ( ) ]H L[ ( ) ( ) ( ) ( ) ]L tiers L H L H L H L H L H L H L H L H Surface M H L H L H D T M H L H L H D B tierDuration tier (+) (++) (+) (++)Figure 1. An example of derivation of prosody from the textFigure2. Resulting F 0 curve。
