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RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
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In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
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In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022)
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Automatic Speech Recognition (ASR) Systems for Children: A Systematic Literature Review
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4419 (2022)
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Discovering Acoustic Units from Speech: A Bayesian Approach ; Découverte d'unités acoustiques dans la parole : une approche Bayésienne
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In: https://hal.archives-ouvertes.fr/tel-03478075 ; Computation and Language [cs.CL]. Brno University of Technology (MAIS), 2021. English (2021)
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| 5 |
Разработка современной системы распознавания русскоязычной телефонной речи ... : Speech recognition system for russian-language telephone speech ...
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| 6 |
Simulation of vowel-vowel utterances using a 3D biomechanical-acoustic model
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Dabbaghchian, Saeed; Arnela, Marc; Engwall, Olov. - : KTH, Tal, musik och hörsel, TMH, 2021. : Universitat Ramon Llull, Barcelona, Catalonia, 2021. : Wiley, 2021
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| 7 |
On the Primary Influences of Age on Articulation and Phonation in Maximum Performance Tasks
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In: Languages ; Volume 6 ; Issue 4 (2021)
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| 8 |
Detrending the Waveforms of Steady-State Vowels
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In: Entropy ; Volume 22 ; Issue 3 (2020)
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| 9 |
Controlling the voice quality dimension of prosody in synthetic speech using an acoustic glottal model
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MURPHY, ANDREW. - : Trinity College Dublin. School of Linguistic Speech & Comm Sci. C.L.C.S., 2020
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| 10 |
Articulatory-WaveNet: Deep Autoregressive Model for Acoustic-to-Articulatory Inversion
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In: Theses and Dissertations--Electrical and Computer Engineering (2020)
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| 11 |
Articulation modelling of vowels in dysarthric and non-dysarthric speech
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| 12 |
Exploring Efficient Neural Architectures for Linguistic–Acoustic Mapping in Text-To-Speech
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In: Applied Sciences ; Volume 9 ; Issue 16 (2019)
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| 13 |
Dealing with linguistic mismatches for automatic speech recognition
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| 14 |
Bayesian models for unit discovery on a very low resource language
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In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01709589 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2018, Calgary, Alberta, Canada (2018)
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| 15 |
Computational Modeling of the Vocal Tract : Applications to Speech Production
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| 16 |
PROSODIC EXPRESSION OF EMOTIONAL-AND-PRAGMATIC POTENTIAL OF A SPOKEN ENGLISH PROVERB
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In: Передовое образование; 2018: ; 169-177 ; Advanced Education; 2018: Issue 9; 169-177 ; Новітня освіта; 2018: ; 2410-8286 ; 2409-3351 (2018)
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| 17 |
Automatic assessment of singing voice pronunciation: a case study with Jingju music
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In: TDX (Tesis Doctorals en Xarxa) (2018)
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| 18 |
A combined evaluation of established and new approaches for speech recognition in varied reverberation conditions
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In: ISSN: 0885-2308 ; EISSN: 1095-8363 ; Computer Speech and Language ; https://hal.inria.fr/hal-01461382 ; Computer Speech and Language, Elsevier, 2017, 46, pp.444-460. ⟨10.1016/j.csl.2017.02.003⟩ (2017)
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| 19 |
Development of the Arabic Loria Automatic Speech Recognition system (ALASR) and its evaluation for Algerian dialect
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In: ACLing 2017 - 3rd International Conference on Arabic Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01583842 ; ACLing 2017 - 3rd International Conference on Arabic Computational Linguistics, Nov 2017, Dubai, United Arab Emirates. pp.1-8 (2017)
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Acoustic sequences in non-human animals : a tutorial review and prospectus
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