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The use of prosodic parameters in automatic speech recognition
Jacqueline Vaissière
To cite this version:
Jacqueline Vaissière. The use of prosodic parameters in automatic speech recognition. H. Niemann
& al. Recent advances in speech understanding and dialog systems, Springer Verlag, pp.71-99, 1988,
NATO ASI Series. �halshs-00363982�
TüE
USE OF PROSODIC PAûhWZTERS IN AUTOMATIC SPEECH RECûûNITION
J . V a h r i b r e
Centre National d'Etud.8 cies T616commuiications 22301 Lannion, France
prosody/ suprasegmental/ automatic speech recognition/ stress/ boun- daries/ junctured segmentation/ phrase/ sentence type
The present cornunication concerns the use of prosodic parameters in automatic speech recognition (ASR), i.e. the feasibility of automatically extracting prosodic information from a set of acoustic measurements done on the signal, and the incidence of integrating such information on the performance of ASR. Prosodic parameters include pauses and contrasta in pitch, duration and intensity between successive segments (mainly the vocalic parts). This notion is also extended to number of syllablas and to ratios of voiced to unvoiced portions of the words. Part one introduces the various aspects of prosody (linguistic and non linguistic) and the main problems to be solved in automatically extracting linguistic mes- sages conveyed by prosodic features. Part two deals with word level and lexical search: it presents work done (1) on the feasibility of word stress detection (primary stress, ertiniation of its magnitude, and evaluation of the complete word stress pattern) and (2) on the estimation of the amount of lexical conrtraints imposed by stress information in lexical search, conipleted by other suprasegmental information (number of syllables, word boundaries, ratios between voiced and unvoiced portion in the word, etc.). Part three deals with phrase and sentence levels and syntactic constraints provided by the automatic detection of word, phrase and sentence boundaries.
Part four relates a number of miscellaneous uses at the phonemic level: phonetic segmentation, identification of the voicing feature of consonabta, and estimation of the "segmenta1 qualityu o f the underlying segments.
It is obssrved that prosodic parameters have been exploired rsther poorly compared to segmental aspects of speech. Integration o f pro-
sodic knowledge with segmental knowledge in an ASR system is a dif- ficult problem: t o know when and where to integrata the prosodia knowledge into the system and how to combine the evidence and scores obtained from different sources. The exact contribution of t h e use of prosody in ASR is still to be estimated in an ASR system flexible enough to efficlently test such an integration.
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