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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Explicit trajectories and speaker class modeling for child and adult speech recognition ; Modélisation de trajectoires et de classes de locuteurs pour la reconnaissance de voix d'enfants et d'adultes Gorin, Arseniy; Jouvet, Denis In: XXXème édition des Journées d'Etudes sur la Parole ; https://hal.inria.fr/hal-01080343 ; XXXème édition des Journées d'Etudes sur la Parole, Jun 2014, Le Mans, France (2014) BASE Show details 2 Component Structuring and Trajectory Modeling for Speech Recognition Gorin, Arseniy; Jouvet, Denis In: Interspeech ; https://hal.inria.fr/hal-01063653 ; Interspeech, Sep 2014, Singapoore, Singapore (2014) Abstract: International audience ; When the speech data are produced by speakers of different age and gender, the acoustic variability of any given phonetic unit becomes large, which degrades speech recognition performance. A way to go beyond the conventional Hidden Markov Model is to explicitly include speaker class information in the modeling. Speaker classes can be obtained by unsupervised clustering of the speech utterances. This paper introduces a structuring of the Gaussian compo- nents of the GMM densities with respect to speaker classes. In a first approach, the structuring of the Gaussian components is combined with speaker class-dependent mixture weights. In a second approach, the structuring is used with mixture transition matrices, which add dependencies between Gaussian components of mixture densities (as in stranded GMMs). The different approaches are evaluated and compared in detail on the TIDIGITS task. Significant improvements are obtained using the proposed approaches based on structured components. Additional results are reported for phonetic decoding on the NEOLOGOS database, a large corpus of French telephone data. Keyword: [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD]; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing URL: https://hal.inria.fr/hal-01063653/document https://hal.inria.fr/hal-01063653/file/inter2014_agorin_v11.pdf https://hal.inria.fr/hal-01063653 BASE Hide details

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