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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 – 1 of 1 1 Pronunciation assessment of Japanese learners of French with GOP scores and phonetic information Laborde, Vincent; Pellegrini, Thomas; Fontan, Lionel; Mauclair, Julie; Sahraoui, Halima; Farinas, Jérôme 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) Abstract: International audience ; In this paper, we report automatic pronunciation assessment experiments at phone-level on a read speech corpus in French, collected from 23 Japanese speakers learning French as a foreign language. We compare the standard approach based on Goodness Of Pronunciation (GOP) scores and phone-specific score thresholds to the use of logistic regressions (LR) models. French native speech corpus, in which artificial pronunciation errors were introduced, was used as training set. Two typical errors of Japanese speakers were considered: /ö/ and /v/ of ten mispronounced as [l] and [b], respectively. The LR classifier achieved a 64.4% accuracy similar to the 63.8% accuracy of the baseline threshold method, when using GOP scores and the expected phone identity as input features only. A significant performance gain of 20.8% relative was obtained by adding phonetic and phonological features as input to the LR model, leading to a 77.1% accuracy. This LR model also outperformed another baseline approach based on linear discriminant models trained on raw f-BANK coefficient features. 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; Automatic pronunciation assessment; Computer-assisted language learning; Goodness of pronunciation URL: https://hal.archives-ouvertes.fr/hal-01474896/file/laborde_17159.pdf https://hal.archives-ouvertes.fr/hal-01474896 https://doi.org/10.21437/Interspeech.2016-513 https://hal.archives-ouvertes.fr/hal-01474896/document BASE Hide details

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