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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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Abstract:
International audience ; The widespread of powerful personal devices capable of collecting voice of their users has opened the opportunity to build speaker adapted speech recognition system (ASR) or to participate to collaborative learning of ASR. In both cases, personalized acoustic models (AM), i.e. fine-tuned AM with specific speaker data, can be built. A question that naturally arises is whether the dissemination of personalized acoustic models can leak personal information. In this paper, we show that it is possible to retrieve the gender of the speaker, but also his identity, by just exploiting the weight matrix changes of a neural acoustic model locally adapted to this speaker. Incidentally we observe phenomena that may be useful towards explainability of deep neural networks in the context of speech processing. Gender can be identified almost surely using only the first layers and speaker verification performs well when using middle-up layers. Our experimental study on the TED-LIUM 3 dataset with HMM/TDNN models shows an accuracy of 95% for gender detection, and an Equal Error Rate of 9.07% for a speaker verification task by only exploiting the weights from personalized models that could be exchanged instead of user data.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; acoustic model; Automatic speech recognition; collaborative learning; personalized acoustic models; speaker information
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URL: https://hal.archives-ouvertes.fr/hal-03539741
https://hal.archives-ouvertes.fr/hal-03539741/document
https://hal.archives-ouvertes.fr/hal-03539741/file/ICASSP_2022_SpeakerAnalysisInfoPrivacyVF.pdf
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| 3 |
Language-Independent Speaker Anonymization Approach using Self-Supervised Pre-Trained Models ...
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| 4 |
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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| 5 |
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: ; INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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| 6 |
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: ; INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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| 7 |
Privacy and utility of x-vector based speaker anonymization
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In: https://hal.inria.fr/hal-03197376 ; 2021 (2021)
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| 8 |
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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| 11 |
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Benchmarking and challenges in security and privacy for voice biometrics
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In: SPSC 2021, 1st ISCA Symposium on Security and Privacy in Speech Communication ; https://hal.archives-ouvertes.fr/hal-03346196 ; SPSC 2021, 1st ISCA Symposium on Security and Privacy in Speech Communication, ISCA, Nov 2021, Magdeburg, Germany. ⟨10.21437/SPSC.2021-11⟩ ; https://spsc-symposium2021.de/#home (2021)
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| 14 |
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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| 16 |
The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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ON-TRAC' systems for the IWSLT 2021 low-resource speech translation and multilingual speech translation shared tasks
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In: Proceedings of the 18th International Conference on Spoken Language Translation, ; International Conference on Spoken Language Translation (IWSLT) ; https://hal.archives-ouvertes.fr/hal-03298854 ; International Conference on Spoken Language Translation (IWSLT), Aug 2021, Bangkok (virtual), Thailand. ⟨10.18653/v1/2021.iwslt-1.20⟩ (2021)
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| 18 |
Privacy and utility of x-vector based speaker anonymization
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In: https://hal.inria.fr/hal-03197376 ; 2021 (2021)
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| 19 |
Anonymous speaker clusters: Making distinctions between anonymised speech recordings with clustering interface
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In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03267084 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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Anonymous speaker clusters: Making distinctions between anonymised speech recordings with clustering interface
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In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03267084 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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