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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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The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units
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In: Interspeech 2020 - Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-02962224 ; Interspeech 2020 - Conference of the International Speech Communication Association, Oct 2020, Shangai / Virtual, China (2020)
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LIBRI-LIGHT: a benchmark for asr with limited or no supervision
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Kahn, Jacob; Rivière, Morgane; Zheng, Weiyi; Kharitonov, Eugene; Xu, Qiantong; Mazaré, Pierre-Emmanuel; Karadayi, Julien; Liptchinsky, Vitaliy; Collobert, Ronan; Fügen, Christian; Likhomanenko, Tatiana; Synnaeve, Gabriel; Joulin, Armand; Abdelrahman, Mohamed,; Dupoux, Emmanuel
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In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-02959460 ; ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2020, Barcelona / Virtual, Spain. pp.7669-7673, ⟨10.1109/ICASSP40776.2020.9052942⟩ (2020)
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Abstract:
International audience ; We introduce a new collection of spoken English audio suitable for training speech recognition systems under limited or no supervision. It is derived from open-source audio books from the LibriVox project. It contains over 60K hours of audio , which is, to our knowledge, the largest freely-available corpus of speech. The audio has been segmented using voice activity detection and is tagged with SNR, speaker ID and genre descriptions. Additionally, we provide baseline systems and evaluation metrics working under three settings: (1) the zero resource/unsupervised setting (ABX), (2) the semi-supervised setting (PER, CER) and (3) the distant supervision setting (WER). Settings (2) and (3) use limited textual resources (10 minutes to 10 hours) aligned with the speech. Setting (3) uses large amounts of unaligned text. They are evaluated on the standard LibriSpeech dev and test sets for comparison with the supervised state-of-the-art. Index Terms-unsupervised and semi-supervised learning , distant supervision, dataset, zero-and low resource ASR.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD]
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URL: https://doi.org/10.1109/ICASSP40776.2020.9052942
https://hal.archives-ouvertes.fr/hal-02959460/document
https://hal.archives-ouvertes.fr/hal-02959460
https://hal.archives-ouvertes.fr/hal-02959460/file/1912.07875.pdf
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The Zero Resource Speech Challenge 2019: TTS without T
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In: Interspeech 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-02274112 ; Interspeech 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019)
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Learning Word Embeddings: Unsupervised Methods for Fixed-size Representations of Variable-length Speech Segments
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In: Interspeech 2018 ; https://hal.archives-ouvertes.fr/hal-01888708 ; Interspeech 2018, Sep 2018, Hyderabad, India. ⟨10.21437/Interspeech.2018-2364⟩ (2018)
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Sampling strategies in Siamese Networks for unsupervised speech representation learning
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In: Interspeech 2018 ; https://hal.archives-ouvertes.fr/hal-01888725 ; Interspeech 2018, Sep 2018, Hyderabad, India (2018)
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A K-nearest neighbours approach to unsupervised spoken term discovery
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In: IEEE Spoken Language Technology SLT-2018 ; https://hal.archives-ouvertes.fr/hal-01947953 ; IEEE Spoken Language Technology SLT-2018, Dec 2018, Athènes, Greece (2018)
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The Zero Resource Speech Challenge 2017
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In: ASRU 2017 ; https://hal.inria.fr/hal-01687504 ; ASRU 2017, Dec 2017, Okinawa, Japan (2017)
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