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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 – 4 of 4 1 CNN-based phone segmentation experiments in a less-represented language Manenti, Céline; Pellegrini, Thomas; Pinquier, Julien In: Proceedings of INTERSPEECH 2016 Volume 2 ; 17th Annual Conference of the International Speech Communication Association (INTERSPEECH 2016) ; https://hal.archives-ouvertes.fr/hal-01500519 ; 17th Annual Conference of the International Speech Communication Association (INTERSPEECH 2016), Sep 2016, San Francisco, United States. pp. 3549-3553 (2016) Abstract: International audience ; These last years, there has been a regain of interest in unsupervised sub-lexical and lexical unit discovery. Speech segmentation into phone-like units may be a first interesting step for such a task. In this article, we report speech segmentation experiments in Xitsonga, a less-represented language spoken in South Africa. We chose to use convolutional neural networks (CNN) with FBANK static coefficients as input. The models take binary decisions whether a boundary is present or not at each signal sliding frame. We compare the use of a model trained exclusively on Xitsonga data to the use of a bootstrap model trained on a larger corpus of another language, the BUCKEYE U.S. English corpus. Using a two-convolution-layer model, a 79% F-measure was obtained on BUCKEYE, with a 20 ms error tolerance. This performance is equal to the human inter-annotator agreement rate. We then used this bootstrap model to segment Xitsonga data and compared the results when adapting it with 1 to 20 minutes of Xitsonga data. Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]; [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]; [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; Convolutional neural networks; Phonemes; Segmentation; Under-resourced languages URL: https://hal.archives-ouvertes.fr/hal-01500519 https://hal.archives-ouvertes.fr/hal-01500519/document https://hal.archives-ouvertes.fr/hal-01500519/file/manenti_17052.pdf BASE Hide details 2 Pronunciation assessment of Japanese learners of French with GOP scores and phonetic information Laborde, Vincent; Pellegrini, Thomas; Fontan, Lionel... In: Proceedings of INTERSPEECH 2016 ; Annual conference Interspeech (INTERSPEECH 2016) ; https://hal.archives-ouvertes.fr/hal-01474896 ; Annual conference Interspeech (INTERSPEECH 2016), Sep 2016, San Francisco, CA, United States. pp.2686-2690, ⟨10.21437/Interspeech.2016-513⟩ (2016) BASE Show details 3 Traitement de la prononciation en langue étrangère : approches didactiques, méthodes automatiques et enjeux pour l'apprentissage Detey, Sylvain; Fontan, Lionel; Pellegrini, Thomas In: ISSN: 1248-9433 ; EISSN: 1965-0906 ; Revue TAL ; https://hal.archives-ouvertes.fr/hal-01919021 ; Revue TAL, ATALA (Association pour le Traitement Automatique des Langues), 2016, 57 (3), pp.15-39 (2016) BASE Show details 4 Inferring phonemic classes from CNN activation maps using clustering techniques Pellegrini, Thomas; Mouysset, Sandrine In: Proceedings of INTERSPEECH 2016 ; Annual conference Interspeech (INTERSPEECH 2016) ; https://hal.archives-ouvertes.fr/hal-01474886 ; Annual conference Interspeech (INTERSPEECH 2016), Sep 2016, San Francisco, United States. pp. 1290-1294 (2016) BASE Show details

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