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Thèse Année : 2016

Acoustic gesture modeling. Application to a Vietnamese speech recognition system

Modélisation des gestes acoustiques. Application à un système de reconnaissance de la parole Vietnamienne

Résumé

Speech plays a vital role in human communication. Selection of relevant acoustic speech features is key to in the design of any system using speech processing. For some 40 years, speech was typically considered as a sequence of quasi-stable portions of signal (vowels) separated by transitions (consonants). Despite a wealth of studies that clearly document the importance of coarticulation, and reveal that articulatory and acoustic targets are not context-independent, the view that each vowel has an acoustic target that can be specified in a context-independent manner remains widespread. This point of view entails strong limitations. It is well known that formant frequencies are acoustic characteristics that bear a clear relationship with speech production, and that can distinguish among vowels. Therefore, vowels are generally described with static articulatory configurations represented by targets in the acoustic space, typically by formant frequencies in F1-F2 and F2-F3 planes. Plosive consonants can be described in terms of places of articulation, represented by locus or locus equations in an acoustic plane. But formant frequencies trajectories in fluent speech rarely display a steady state for each vowel. They vary with speaker, consonantal environment (co-articulation) and speaking rate (relating to continuum between hypo- and hyper-articulation). In view of inherent limitations of static approaches, the approach adopted here consists in studying both vowels and consonants from a dynamic point of view.Firstly we studied the effects of the impulse response at the beginning, at the end and during transitions of the signal both in the speech signal and at the perception level. Variations of the phases of the components were then examined. Results show that the effects of these parameters can be observed in spectrograms. Crucially, the amplitudes of the spectral components distinguished under the approach advocated here are sufficient for perceptual discrimination. From this result, for all speech analysis, we only focus on amplitude domain, deliberately leaving aside phase information. Next we extent the work to vowel-consonant-vowel perception from a dynamic point of view. These perceptual results, together with those obtained earlier by Carré (2009a), show that vowel-to-vowel and vowel-consonant-vowel stimuli can be characterized and separated by the direction and rate of the transitions on formant plane, even when absolute frequency values are outside the vowel triangle (i.e. the vowel acoustic space in absolute values).Due to limitations of formant measurements, the dynamic approach needs to develop new tools, based on parameters that can replace formant frequency estimation. Spectral Subband Centroid Frequency (SSCF) features was studied. Comparison with vowel formant frequencies show that SSCFs can replace formant frequencies and act as “pseudo-formant” even during consonant production.On this basis, SSCF is used as a tool to compute dynamic characteristics. We propose a new way to model the dynamic speech features: we called it SSCF Angles. Our analysis work on SSCF Angles were performed on transitions of vowel-to-vowel (V1V2) sequences of both Vietnamese and French. SSCF Angles appear as reliable and robust parameters. For each language, the analysis results show that: (i) SSCF Angles can distinguish V1V2 transitions; (ii) V1V2 and V2V1 have symmetrical properties on the acoustic domain based on SSCF Angles; (iii) SSCF Angles for male and female are fairly similar in the same studied transition of context V1V2; and (iv) they are also more or less invariant for speech rate (normal speech rate and fast one). And finally, these dynamic acoustic speech features are used in Vietnamese automatic speech recognition system with several obtained interesting results.
La sélection de caractéristiques acoustiques appropriées est essentielle dans tout système de traitement de la parole. Pendant près de 40 ans, la parole a été généralement considérée comme une séquence de signaux quasi-stables (voyelles) séparés par des transitions (consonnes). Bien qu‟un grand nombre d'études documentent clairement l'importance de la coarticulation, et révèlent que les cibles articulatoires et acoustiques ne sont pas indépendantes du contexte, l‟hypothèse que chaque voyelle présente une cible acoustique qui peut être spécifiée d'une manière indépendante du contexte reste très répandue. Ce point de vue implique des limitations fortes. Il est bien connu que les fréquences de formants sont des caractéristiques acoustiques qui présentent un lien évident avec la production de la parole, et qui peuvent participer à la distinction perceptive entre les voyelles. Par conséquent, les voyelles sont généralement décrites avec des configurations articulatoires statiques représentées par des cibles dans l'espace acoustique, généralement par les fréquences des formants correspondants, représentées dans les plans F1-F2 et F2-F3. Les consonnes occlusives peuvent être décrites en termes de point d'articulation, représentés par locus (ou locus équations) dans le plan acoustique. Mais les trajectoires des fréquences de formants dans la parole fluide présentent rarement un état d'équilibre pour chaque voyelle. Elles varient avec le locuteur, l'environnement consonantique (co-articulation) et le débit de parole (relative à un continuum entre hypo et hyper-articulation). En vue des limites inhérentes aux approches statiques, la démarche adoptée ici consiste à étudier les transitions entre les voyelles et les consonnes (V1V2 et V1CV2) d‟un point de vue dynamique.
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Dates et versions

tel-01599038 , version 1 (01-10-2017)

Identifiants

  • HAL Id : tel-01599038 , version 1

Citer

Thi-Anh-Xuan Tran. Acoustic gesture modeling. Application to a Vietnamese speech recognition system. Signal and Image processing. Université Grenoble Alpes; Institut Polytechnique (Hanoï), 2016. English. ⟨NNT : 2016GREAT023⟩. ⟨tel-01599038⟩
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