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Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding
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In: ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-03578503 ; ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, May 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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Differentially private speaker anonymization
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In: https://hal.inria.fr/hal-03588932 ; 2022 (2022)
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A Study of F0 Modification for X-Vector Based Speech Pseudonymization Across Gender
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In: PPAI 2021 - The Second AAAI Workshop on Privacy-Preserving Artificial Intelligence ; https://hal.archives-ouvertes.fr/hal-02995862 ; PPAI 2021 - The Second AAAI Workshop on Privacy-Preserving Artificial Intelligence, Feb 2021, Virtual, China (2021)
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Assessment of adult speech disorders: current situation and needs in French-speaking clinical practice
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In: ISSN: 1401-5439 ; Logopedics Phoniatrics Vocology ; https://hal.archives-ouvertes.fr/hal-03120115 ; Logopedics Phoniatrics Vocology, Taylor & Francis, 2021, pp.1-15. ⟨10.1080/14015439.2020.1870245⟩ (2021)
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Utterance partitioning for speaker recognition: an experimental review and analysis with new findings under GMM-SVM framework
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In: ISSN: 1381-2416 ; EISSN: 1572-8110 ; International Journal of Speech Technology ; https://hal.archives-ouvertes.fr/hal-03232723 ; International Journal of Speech Technology, Springer Verlag, In press, ⟨10.1007/s10772-021-09862-8⟩ (2021)
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Alternate Endings: Improving Prosody for Incremental Neural TTS with Predicted Future Text Input
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In: Interspeech 2021 - 22nd Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03372802 ; Interspeech 2021 - 22nd Annual Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic. pp.3865-3869, ⟨10.21437/Interspeech.2021-275⟩ (2021)
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Speaker Attentive Speech Emotion Recognition
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In: Proccedings of interspeech 2021 ; Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03554368 ; Interspeech 2021, Aug 2021, Brno, Czech Republic. pp.2866-2870, ⟨10.21437/interspeech.2021-573⟩ (2021)
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EVOLEX : la reconnaissance vocale au service du diagnostic des dysfonctionnements langagiers
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In: Séminaire AFCP 2021 – Phonétique Clinique ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03269242 ; Séminaire AFCP 2021 – Phonétique Clinique, May 2021, Toulouse (virtuel), France ; http://www.afcp-parole.org/seminaire-afcp-phonetique-clinique-27-mai-2021/ (2021)
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Recognizing lexical units in low-resource language contexts with supervised and unsupervised neural networks
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In: https://hal.archives-ouvertes.fr/hal-03429051 ; [Research Report] LACITO (UMR 7107). 2021 (2021)
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Automatic extraction of speech rhythm descriptors for speech intelligibility assessment in the context of Head and Neck Cancers
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In: à paraître ; INTERSPEECH 2021 ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03269227 ; INTERSPEECH 2021, ISCA : International Speech and Communication Association, Aug 2021, Brno, Czech Republic ; https://www.interspeech2021.org (2021)
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Prosodic Boundary Prediction Model for Vietnamese Text-To-Speech
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In: Proc. Interspeech 2021 ; Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03329116 ; Interspeech 2021, Aug 2021, Brno, Czech Republic. pp.3885-3889, ⟨10.21437/interspeech.2021-125⟩ (2021)
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“Motherese” Prosody in Fetal-Directed Speech: An Exploratory Study Using Automatic Social Signal Processing
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In: ISSN: 1664-1078 ; Frontiers in Psychology ; https://hal.sorbonne-universite.fr/hal-03184038 ; Frontiers in Psychology, Frontiers, 2021, 12, ⟨10.3389/fpsyg.2021.646170⟩ (2021)
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Learning spectro-temporal representations of complex sounds with parameterized neural networks
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In: ISSN: 0001-4966 ; EISSN: 1520-8524 ; Journal of the Acoustical Society of America ; https://hal.inria.fr/hal-03329261 ; Journal of the Acoustical Society of America, Acoustical Society of America, 2021, 150 (1), pp.353-366. ⟨10.1121/10.0005482⟩ (2021)
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Modeling the effect of military oxygen masks on speech characteristics
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In: Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03325087 ; Interspeech 2021, Aug 2021, Brno, Czech Republic (2021)
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MRI Vocal Tract Sagittal Slices Estimation during Speech Production of CV
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In: EUSIPCO 2020 - 28th European Signal Processing Conference ; https://hal.inria.fr/hal-03090824 ; EUSIPCO 2020 - 28th European Signal Processing Conference, Jan 2021, Amsterdam / Virtual, Netherlands ; https://eusipco2020.org/ (2021)
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Construction of an automatic score for the evaluation of speech disorders among patients treated for a cancer of the oral cavity or the oropharynx: The Carcinologic Speech Severity Index
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In: ISSN: 1043-3074 ; EISSN: 1097-0347 ; Head and Neck ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03413678 ; Head and Neck, Wiley, In press, ⟨10.1002/hed.26903⟩ (2021)
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Automated Assessment of Glottal Dysfunction Through Unified Acoustic Voice Analysis
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In: ISSN: 0892-1997 ; Journal of Voice ; https://hal.archives-ouvertes.fr/hal-02987882 ; Journal of Voice, Elsevier, In press, ⟨10.1016/j.jvoice.2020.08.032⟩ (2021)
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Leveraging lyrics from audio for MIR ; Exploiter les paroles de chansons à partir de l'audio pour le MIR
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In: https://tel.archives-ouvertes.fr/tel-03558515 ; Signal and Image processing. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAT027⟩ (2021)
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On the effect of normalization layers on Differentially Private training of deep Neural networks
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In: https://hal.inria.fr/hal-03475600 ; 2021 (2021)
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Abstract:
Differentially private stochastic gradient descent (DPSGD) is a variation of stochastic gradient descent based on the Differential Privacy (DP) paradigm, which can mitigate privacy threats that arise from the presence of sensitive information in training data. However, one major drawback of training deep neural networks with DPSGD is a reduction in the models accuracy. In this paper, we study the effect of normalization layers on the performance of DPSGD. We demonstrate that normalization layers significantly impact the utility of deep neural networks with noisy parameters and should be considered essential ingredients of training with DPSGD. In particular, we propose a novel method for integrating batch normalization with DPSGD without incurring an additional privacy loss. With our approach, we are able to train deeper networks and achieve a better utility-privacy trade-off.
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Keyword:
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
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URL: https://hal.inria.fr/hal-03475600
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