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A Bottleneck Auto-Encoder for F0 Transformations on Speech and Singing Voice
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In: ISSN: 2078-2489 ; Information ; https://hal.archives-ouvertes.fr/hal-03599085 ; Information, MDPI, 2022, 13 (3), pp.102. ⟨10.3390/info13030102⟩ (2022)
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Neural Vocoding for Singing and Speaking Voices with the Multi-Band Excited WaveNet
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In: ISSN: 2078-2489 ; Information ; https://hal.archives-ouvertes.fr/hal-03599076 ; Information, MDPI, 2022, 13 (3), pp.103. ⟨10.3390/info13030103⟩ (2022)
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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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| 5 |
Etude de cas de pathologies de la parole dans le cadre de la prise en charge orthophonique
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In: https://hal.archives-ouvertes.fr/hal-03568182 ; 2022 (2022)
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Computational models of disfluencies : fillers and discourse markers in spoken language understanding ; Modèles computationnels des disfluences dans le traitement de la parole
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In: https://tel.archives-ouvertes.fr/tel-03653211 ; Computer science. Institut Polytechnique de Paris, 2022. English. ⟨NNT : 2022IPPAT001⟩ (2022)
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| 7 |
Differentially private speaker anonymization
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In: https://hal.inria.fr/hal-03588932 ; 2022 (2022)
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Abstract:
Sharing real-world speech utterances is key to the training and deployment of voice-based services. However, it also raises privacy risks as speech contains a wealth of personal data. Speaker anonymization aims to remove speaker information from a speech utterance while leaving its linguistic and prosodic attributes intact. State-of-the-art techniques operate by disentangling the speaker information (represented via a speaker embedding) from these attributes and re-synthesizing speech based on the speaker embedding of another speaker. Prior research in the privacy community has shown that anonymization often provides brittle privacy protection, even less so any provable guarantee. In this work, we show that disentanglement is indeed not perfect: linguistic and prosodic attributes still contain speaker information. We remove speaker information from these attributes by introducing differentially private feature extractors based on an autoencoder and an automatic speech recognizer, respectively, trained using noise layers. We plug these extractors in the state-of-the-art anonymization pipeline and generate, for the first time, differentially private utterances with a provable upper bound on the speaker information they contain. We evaluate empirically the privacy and utility resulting from our differentially private speaker anonymization approach on the LibriSpeech data set. Experimental results show that the generated utterances retain very high utility for automatic speech recognition training and inference, while being much better protected against strong adversaries who leverage the full knowledge of the anonymization process to try to infer the speaker identity.
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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-03588932
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| 8 |
Automatic assessment of oral readings of young pupils
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In: ISSN: 0167-6393 ; EISSN: 1872-7182 ; Speech Communication ; https://hal.archives-ouvertes.fr/hal-03585934 ; Speech Communication, Elsevier : North-Holland, 2022, 138, pp.67-79. ⟨10.1016/j.specom.2022.01.008⟩ ; https://www.sciencedirect.com/science/article/pii/S0167639322000164?via%3Dihub (2022)
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| 9 |
Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition ...
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| 10 |
Decoding Neural Correlation of Language-Specific Imagined Speech using EEG Signals ...
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| 11 |
Multi Antenna Radar System for American Sign Language (ASL) Recognition Using Deep Learning ...
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| 12 |
Effect of Kinematics and Fluency in Adversarial Synthetic Data Generation for ASL Recognition with RF Sensors ...
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Separate What You Describe: Language-Queried Audio Source Separation ...
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| 15 |
CALM: Contrastive Aligned Audio-Language Multirate and Multimodal Representations ...
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| 16 |
Mutual Understanding in Situated Interactions with Conversational User Interfaces : Theory, Studies, and Computation
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| 17 |
Segmentation of Glottal Images from High-Speed Videoendoscopy Optimized by Synchronous Acoustic Recordings
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In: Sensors; Volume 22; Issue 5; Pages: 1751 (2022)
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| 18 |
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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| 19 |
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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| 20 |
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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