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1
Differentially private speaker anonymization
In: https://hal.inria.fr/hal-03588932 ; 2022 (2022)
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The VoicePrivacy 2022 Challenge Evaluation Plan ...
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Analyzing the impact of speaker localization errors on speech separation for automatic speech recognition
In: EUSIPCO 2020 - 28th European Signal Processing Conference ; https://hal.inria.fr/hal-02355669 ; EUSIPCO 2020 - 28th European Signal Processing Conference, Jan 2021, Amsterdam / Virtual, Netherlands. ⟨10.23919/Eusipco47968.2020.9287541⟩ ; https://eusipco2020.org/ (2021)
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On Refining BERT Contextualized Embeddings using Semantic Lexicons
In: Machine Learning with Symbolic Methods and Knowledge Graphs co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021) ; https://hal.archives-ouvertes.fr/hal-03318571 ; Machine Learning with Symbolic Methods and Knowledge Graphs co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Sep 2021, Online, Spain (2021)
Abstract: International audience ; Word vector representations play a fundamental role in many NLP applications. Exploiting human-curated knowledge was proven to improve the quality of word embeddings and their performance on many downstream tasks. Retrofitting is a simple and popular technique for refining distributional word embeddings based on relations coming from a semantic lexicon. Inspired by this technique, we present two methods for incorporating knowledge into contextualized embeddings. We evaluate these methods with BERT embeddings on three biomedical datasets for relation extraction and one movie review dataset for sentiment analysis. We demonstrate that the retrofitted vectors do not substantially impact the performance for these tasks, and conduct a qualitative analysis to provide further insights on this negative result.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; BERT; Contextualized embeddings; Knowledge integration; Qualitative analysis; Retrofitting
URL: https://hal.archives-ouvertes.fr/hal-03318571
https://hal.archives-ouvertes.fr/hal-03318571/file/On_Refining_BERT_Contextualized_Embeddings_using_Semantic_Lexicons__CSSA.pdf
https://hal.archives-ouvertes.fr/hal-03318571/document
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5
Privacy and utility of x-vector based speaker anonymization
In: https://hal.inria.fr/hal-03197376 ; 2021 (2021)
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6
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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7
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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8
The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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9
Transformer versus LSTM Language Models Trained on Uncertain ASR Hypotheses in Limited Data Scenarios
In: https://hal.inria.fr/hal-03362828 ; 2021 (2021)
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10
Enabling voice-based apps with European values
In: ISSN: 0926-4981 ; ERCIM News ; https://hal.inria.fr/hal-03476390 ; ERCIM News, ERCIM, 2021, 126, pp.38-39 ; https://ercim-news.ercim.eu/images/stories/EN126/EN126-web.pdf (2021)
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11
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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12
The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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13
Enhancing Speech Privacy with Slicing
In: https://hal.inria.fr/hal-03369137 ; 2021 (2021)
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14
Benchmarking and challenges in security and privacy for voice biometrics
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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15
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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16
Training RNN Language Models on Uncertain ASR Hypotheses in Limited Data Scenarios
In: https://hal.inria.fr/hal-03327306 ; 2021 (2021)
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17
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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18
The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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19
Adapting Language Models When Training on Privacy-Transformed Data
In: INTERSPEECH 2021 ; https://hal.inria.fr/hal-03189354 ; 2021 (2021)
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20
Privacy and utility of x-vector based speaker anonymization
In: https://hal.inria.fr/hal-03197376 ; 2021 (2021)
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