Skip to main content

Morpho-Syntactic Analysis

  • Chapter
  • 360 Accesses

Part of the book series: Text, Speech and Language Technology ((TLTB,volume 3))

Abstract

Chapters Five and Six will highlight the need for some syntactic processing in a high-quality text-to-speech system. Being able to reduce a given sentence into something like the sequence of its parts of speech, and to further describe it in the form of a syntax tree, which unveils its internal structure, is required for at least two reasons:

  • Accurate phonetic transcription can be achieved only if the part of speech category of some words is available, and may depend on knowing the dependency relationship between successive words.

  • Natural prosody heavily relies on syntax. It also obviously has a lot to do with semantics and pragmatics, but since very little data is currently available on the generative aspects of this dependence, TTS systems merely concentrate on syntax. Yet, as we shall see, few of them are actually provided with full disambiguation and structuring capabilities.

‘Twas brillig, and the slithy toves Did gyre and gimble in the wabes: All mimst were the borogroves, And the mome raths outgrabe. Lewis Carroll, Jabberwocky

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • ALLEN, J., S. HUNNICUT, and D. KLATT, (1987), From Text To Speech, The MITALK System, Cambridge University Press, Cambridge.

    Google Scholar 

  • ALLEN, J., (1992), “Overview of Text-to-Speech Systems”, in Advances in Speech Signal Processing, S. Furui and M. Sondhi, eds., Dekker, New York, pp. 741–790.

    Google Scholar 

  • BENELLO, J., A.W. MACKIE, and J.A. ANDERSON, (1989), “Syntactic Category Disambiguation with Neural Networks”, Computer Speech and Language, n°3, pp. 203–217.

    Google Scholar 

  • BLOIS, J., and J. BUYDENS, (1968), Problèmes de la Traduction Automatique, Klinckslieck, Paris.

    Google Scholar 

  • BÖHM, A., (1992), Maschinelle Sprachausgabe Deutschen und Englishe Textes, Ph.D. dissertation, Ruhr-Universität Bochum.

    Google Scholar 

  • BRIEMAN, L., J.H. FRFFIDMAN, R.A. OLSHEN, and C.J. STONE, (1984), Classification and Regression Trees, 1984, Wadsworth & Brooks, Monterey, CA.

    Google Scholar 

  • BRILL, E., (1994), “Some Advances in Transformation-based Part of Speech Tagging”, to appear in Proceedings of the AAAI’94, also on CMP-LG, paper n° 940601033.

    Google Scholar 

  • CERF-DANON, H., and M. ELBEZE, (1991), “Three Different Probabilistic Language Models: Comparison and Combination”, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing 91, Toronto, pp. 297–300.

    Google Scholar 

  • CHURCH, K. W., (1987), Phonological Parsing in Speech Recognition, Kluwer

    Book  Google Scholar 

  • CHURCH, K. W., (1988), “A Stochastic Parts Program and Noun Phrase Parser for Unrestricted Text”, Proceedings of the Second Conference on Applied Natural Language Processing, Austin, Texas.

    Google Scholar 

  • CLEEREMANS, A., D. SERVAN-SCHREIBER, and J.L McCLELLAND, (1989), “Finite-State Automata and Simple Recurrent Networks”, Neural Computation, vol. 1, pp. 372–382.

    Article  Google Scholar 

  • CRYSTAL, D., (1985), A Dictionary of Linguistics and Phonetics, Basil Blackwell.

    Google Scholar 

  • DELIGNE, S., and F. BIMBOT, (1995), “Language Modeling by Variable Length Sequences: Theoretical Formulation and Evaluation of Multigrams”, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing 95, vol. 1, pp. 169–172.

    Google Scholar 

  • DeROSE, S., (1988), “Grammatical Category Disambiguation by Statistical Optimization”, Computational Linguistics, n°14, pp. 31–39.

    Google Scholar 

  • DUMOUCHEL, P., V. GUPTA, M. LENNIG, and P. MERMELSTEIN, (1988), “Three Probabilistic Models for a Large-Vocabulary Speech Recognizer”, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing 88, New-York, pp. 513–516.

    Google Scholar 

  • DUTOIT, T., (1993), High Quality Text-To-Speech Synthesis of the French Language, Ph. D. dissertation, Faculté Polytechnique de Mons.

    Google Scholar 

  • FROIDEVEAUX, C., M.-C. GAUDEL, and M.SORIA, (1990), Types de Données et Algorithmes, McGraw-Hill, Paris, 577 pp.

    Google Scholar 

  • GARSIDE, R., G. LEECH, and G. SAMPSON, (1987), The Computational Analysis of English, Longman, London.

    Google Scholar 

  • GAZDAR, G., and C. MELLISH, (1989), Natural Language Processing in Prolog: an Introduction to Computional Linguistics, Addison-Wesley, Reading, MA.

    Google Scholar 

  • GREENE, B.B., and G.M. RUBIN, (1977), “Automatic Grammatical Tagging of English”, Department of Linguistics, Brown University, Providence, Rhode Island.

    Google Scholar 

  • GROSS, M., (1986), Grammaire Transformationnelle du Frangais I. Syntaxe du Verbe. II. Syntaxe du Nom., Cantilène, Paris.

    Google Scholar 

  • GULIKERS, L., and R. WILLEMSE, (1992), “A Lexicon for a Text-to-Speech System”, Proeedings.of the International Conference on Spoken Language Processing, Alberta, pp 101–104.

    Google Scholar 

  • INALF, (1984), Dictionnaire des Fréquences: Table de Répartition des Homographes, CNRS – INALF (institut national de la langue francaise), Nancy.

    Google Scholar 

  • JELINEK, F., (1976), “Continuous Speech Recognition by Statistical Methods”, Proceedings of the IEEE, vol. 64, n°4, pp. 532–556.

    Article  Google Scholar 

  • JELINEK, F., (1991), “Up from Trigrams!”, Proceedings of Eurospeech 91, Genova, vol. 3, pp. 1037–1040.

    Google Scholar 

  • JELINEK, F., R.L. MERCER, and S. ROUKOS, (1992), “Principles of Lexical Language Modeling for Speech Recognition”, in Advances in Speech Signal Processing, S. Furuy and M. Sondhi, eds., Dekker, New York.

    Google Scholar 

  • KARLSSON, F., (1990), “Constraint Grammars as a Framework for Parsing Running Text”, Proceedings of the Conference on Computational Linguistics, Helsinki, vol. 3, pp. 168–173.

    Google Scholar 

  • KARTUNNEN, L., K. KOSKENNIEMI, and R. KAPLAN, (1987), “A Compiler for Two-Level Phonological Rules”. In: Daylrimple et al., Tools for Morphological Analysis, Report N° CSLI-87-108, Center for Study of Language and Information, Stanford University.

    Google Scholar 

  • KNUTH, D., (1973), The Art of Computer Programming, vol. 2, Addison-Wesley, Reading, MA.

    Google Scholar 

  • KOSKENNIEMI, K., (1983), Two Level Morphology: A general Computational Model for Word-Form Recognition and Production, Ph.D. dissertation, Department of General Linguistics, University of Helsinki.

    Google Scholar 

  • KOSKENNIEMI, K., (1990), “Finite-State Parsing and Disambiguation”, Proeedings. of the Conference on Computational Linguistics, Helsinki, vol. 2, pp. 229–232.

    Google Scholar 

  • KUHN, T., H.NIEMANN, and E.G. SHUKAT-TALAMAZZINI, (1994), “Ergodic Hidden Markov Models and Polygrams for Language Modeling”, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing 94, vol. 1, pp. 357–360.

    Google Scholar 

  • KUPIEC, J., (1992), “Robust Part-of-Speech Tagging Using a Hidden Markov Model”, Computer Speech and Language, n°6, pp. 225–242.

    Google Scholar 

  • LARREUR, D., F. EMERARD, F. MARTY, (1989), “Linguistic and Prosodic Processing for a Text-to-Speech Synthesis System” Proceedings of Eurospeech 89, Paris, pp. 510–513.

    Google Scholar 

  • LIBERMAN, M.Y., and K.W. CHURCH, (1992), “Text Analysis and Word Pronunciation in Text-to-Speech Systems”, in Advances in Speech Signal Processing, S. Furui and M. Sondhi, eds., Dekker, New York, pp. 791–831.

    Google Scholar 

  • LINDSTRÖM, A., M. LJUNGQVIST, and K. GUSTAFSONN, (1993), “A Modular Architecture Suppoorting Multiple Hypotheses for Conversion of Text to Phonetic and Linguistic Entities”, Proceedings of Eurospeech 93, Berlin, pp. 1463–1466.

    Google Scholar 

  • LINDSTRÖM, A., and M. LJUNGQVIST, (1994), “Text Processing within a Speech Synthesis System”, Proc. Proceedings, of the International Conference on Spoken Language Processing 94, Yokohama.

    Google Scholar 

  • MASTROLONARDO, A., and M. REFICE, (1989), “Measuring the Power of Self-Organized Linguistic Models”, Proceedings of Eurospeech 89, Paris, vol. 1, pp. 390–393.

    Google Scholar 

  • McALLISTER, M., (1989), “The Problems of Punctuation Ambiguity in Full Automatic Text-to-Speech Conversion”, Proceedings of Eurospeech 89, Paris, vol. 1, pp. 538–541.

    Google Scholar 

  • MERIALDO, B., (1991), “Tagging Text with a Probabilistic Model”, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing 91, pp. 809–812.

    Google Scholar 

  • MOHRI, M., (1994), “Syntactic Analysis by Local Grammars Automata: an Efficient Algorithm”, to appear in the Proceedings ofComplex94. Also on CMP-LG, paper n° 9407002.

    Google Scholar 

  • O’MALLEY, M.H., D.K. LARKIN, and E.W. PETERS, (1986), “Beyond the Reading Machine: What the Next Generation of Intelligent Text-To-Speech Systems Should do for the User”, Proceedings of Speech Technology 86, pp. 216–219.

    Google Scholar 

  • O’SHAUGHNESSY, D., (1987), “Specifying Intonation in a Text-to-Speech System Using Only a Small Dictionary”, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing 87, pp. 1430–1433.

    Google Scholar 

  • PACHUNKE, T., O. MERTINEIT, K. WOTHKE, and R. SCHMIDT, (1994), “The Linguistic Knowledge in a Morphological Segmentation Procedure of German”, Computer Speech and Language, vol. 8, pp. 233–245.

    Article  Google Scholar 

  • PITRAT, J., (1983), Réalisation d’un Analyseur Léxicographique Général, rapport de recherche n°79/2, GR22, Institut de programmation, Paris VI.

    Google Scholar 

  • RILEY, M.D., (1990), “Tree-Based Modeling for Speech Synthesis”, Proceedings of the ESCA Workshop on Speech Synthesis, Autrans (France), pp. 269–272.

    Google Scholar 

  • RIVEST, R.L., (1987), “Learning Decision Lists”, Machine Learning, 2, pp. 229–246.

    MathSciNet  Google Scholar 

  • RÜHL, H.-W., (1984), Sprachsynthese nach Regeln ßr Unbeschränkten Deutschen Text, PhD dissertation, Ruhr-Universtät Bochum.

    Google Scholar 

  • SABAH, G., (1989), L’intelligence Artificielle et le Langage, Tome 1: Répresentation des Connaissances, Tomel: Processus de Compréhension, Hermes, Paris.

    Google Scholar 

  • SENDERS, W., M. KUGLER, and L. BOVES, (1989), “Simultaneous Optimization of Several Variables in a Probabilistic Language Model”, Proceedings of Eurospeech 89, Paris, vol. 2, pp. 63–67.

    Google Scholar 

  • SHIKANO, K., (1987), “Improvement of Word Recognition Results by Trigram Model”, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing 87, pp. 1261–1264.

    Google Scholar 

  • SORIN, C, D. LARREUR, and R. LLORCA, (1987), “A Rhythm-Based Prosodic Parser for Text-to-Speech Systems in French”, Proceedings of the 11th International Congress on Phonetic Sciences, Tallin, vol.1, 125–128.

    Google Scholar 

  • SPROAT, R., J. HIRSHBERG, and D. YAROWSKY, (1992), “A Corpus-Based Synthesizer”, Proc. Proceedings.of the International Conference on Spoken Language Processing 92 Alberta, pp. 563–566.

    Google Scholar 

  • TAPANAINEN, P., and A. VOUTILAINEN, (1994), “Tagging Accurately — Don’t Guess if you Know”, CMP-LG, paper n° 9408009.

    Google Scholar 

  • TRABER, C., (1993), “Syntactic Processing and Prosody Control in the SVOX TTS System for German”, Proceedings of Eurospeech 93, Berlin, vol. 3, pp. 2099–2102.

    Google Scholar 

  • WEISCHEDEL, R., M. METEER, R. SCHWARTZ, L. RAMSHAW, and J. PALMUCCI, (1993), “Coping with Ambiguity and Unknown Wordsthrough Probabilistic Models”, Computational Linguistics, 1994.

    Google Scholar 

  • WILLEMSE, R., and L. GULIKERS, (1992), “Word Class Assignment in a Text-to-Speech System”, Proceedings.of the International Conference on Spoken Language Processing, Alberta, pp. 105–108.

    Google Scholar 

  • WINOGRAD, T., (1972), Understanding Natural Language, Academic Press, Edimburgh.

    Google Scholar 

  • YAROWSKY, D., (1994), “Homograph Disambiguation in Speech Synthesis”, Proceedings of the 2nd ESCA/IEEE Workshop on Speech Synthesis, New Paltz, NY.

    Google Scholar 

  • ZINGLE, H., (1990), “Morphological Segmentation and Stress Calculus in German with an Expert System”, Proceedings of the ESCA Workshop on Speech Synthesis, Autrans (France), pp. 133–136.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Dutoit, T. (1997). Morpho-Syntactic Analysis. In: An Introduction to Text-to-Speech Synthesis. Text, Speech and Language Technology, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5730-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-94-011-5730-8_4

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-0369-1

  • Online ISBN: 978-94-011-5730-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics