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1
Simulating reading mistakes for child speech Transformer-based phone recognition
In: Annual Conference of the International Speech Communication Association (INTERSPEECH) ; https://hal.archives-ouvertes.fr/hal-03257870 ; Annual Conference of the International Speech Communication Association (INTERSPEECH), Aug 2021, Brno, Czech Republic (2021)
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2
Phoneme-to-Audio Alignment with Recurrent Neural Networks for Speaking and Singing Voice
In: Proceedings of Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03552964 ; Proceedings of Interspeech 2021, International Speech Communication Association, Aug 2021, Brno, Czech Republic. pp.61-65, ⟨10.21437/interspeech.2021-1676⟩ ; https://www.interspeech2021.org/ (2021)
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3
End-to-end acoustic modelling for phone recognition of young readers
In: ISSN: 0167-6393 ; EISSN: 1872-7182 ; Speech Communication ; https://hal.archives-ouvertes.fr/hal-03373156 ; Speech Communication, Elsevier : North-Holland, 2021, 134, pp.71-84. ⟨10.1016/j.specom.2021.08.003⟩ ; https://www.sciencedirect.com/science/article/pii/S0167639321000959?via%3Dihub (2021)
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4
Accented Speech Recognition Based on End-to-End Domain Adversarial Training of Neural Networks
In: Applied Sciences ; Volume 11 ; Issue 18 (2021)
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5
Dealing with linguistic mismatches for automatic speech recognition
Yang, Xuesong. - 2019
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