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1
Emotional Speech Recognition Using Deep Neural Networks
In: ISSN: 1424-8220 ; Sensors ; https://hal.archives-ouvertes.fr/hal-03632853 ; Sensors, MDPI, 2022, 22 (4), pp.1414. ⟨10.3390/s22041414⟩ (2022)
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2
Reconnaissance de la parole continue à grand vocabulaire en vietnamien, une langue syllabique tonale
In: Les Journées d’Etude sur la Parole (JEP) ; https://hal.archives-ouvertes.fr/hal-01314293 ; Les Journées d’Etude sur la Parole (JEP), Jun 2008, Avignon, France (2008)
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Synthèse de la parole : = Speech synthesis
Losik, George (Mitarb.); Ovcharenko, Elena B. (Mitarb.); Ipatov, J.V. (Mitarb.)...
In: ICPhS <12, 1991, Aix-en-Provence>. Proceedings of the XIIth International Congress of Phonetic Sciences ; 2. Lundi 19 août. - Aix-en-Provence : Univ. de Provence, Service de Publ. (1991), 494-529
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4
Linear F0 Contour Model For Vietnamese Tones And Vietnamese Syllable Synthesis With TD-PSOLA
In: http://mrim.imag.fr/publications/2006/XUA06/TAL2006SubmissionUpdate.pdf
Abstract: Understanding and managing tonal characteristics of Vietnamese language is one of the most difficult aspects in Vietnamese speech processing. Our newest results indicate that, the initial consonant of one Vietnamese syllable does not carry information of the tone, the Vietnamese tone has an effect only on the Final part of the syllable. Based on obtained results, this article proposes linear F0 contour models for the Vietnamese tones generation. These models only describe the F0 evolution of a final part of the Vietnamese syllable, and they are evaluated through perception tests. 1.
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.492.5987
http://mrim.imag.fr/publications/2006/XUA06/TAL2006SubmissionUpdate.pdf
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