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The Zero Resource Speech Challenge 2021: Spoken language modelling
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In: ISSN: 0162-8828 ; IEEE Transactions on Pattern Analysis and Machine Intelligence ; https://hal.inria.fr/hal-03329301 ; IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2021, pp.1-1. ⟨10.1109/TPAMI.2021.3083839⟩ (2021)
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The Zero Resource Speech Challenge 2021: Spoken language modelling
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In: Interspeech 2021 - Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-03329301 ; Interspeech 2021 - Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic. ⟨10.1109/TPAMI.2021.3083839⟩ (2021)
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The Zero Resource Speech Challenge 2021: Spoken language modelling ...
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The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling
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In: NeuRIPS Workshop on Self-Supervised Learning for Speech and Audio Processing ; https://hal.archives-ouvertes.fr/hal-03070362 ; NeuRIPS Workshop on Self-Supervised Learning for Speech and Audio Processing, Dec 2020, Virtuel, France (2020)
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The Perceptimatic English Benchmark for Speech Perception Models
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In: CogSci 2020 - 42nd Annual Virtual Meeting of the Cognitive Science Society ; https://hal.archives-ouvertes.fr/hal-03087248 ; CogSci 2020 - 42nd Annual Virtual Meeting of the Cognitive Science Society, Jul 2020, Toronto / Virtual, Canada (2020)
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Abstract:
International audience ; We present the Perceptimatic English Benchmark, an open experimental benchmark for evaluating quantitative models of speech perception in English. The benchmark consists of ABX stimuli along with the responses of 91 American Englishspeaking listeners. The stimuli test discrimination of a large number of English and French phonemic contrasts. They are extracted directly from corpora of read speech, making them appropriate for evaluating statistical acoustic models (such as those used in automatic speech recognition) trained on typical speech data sets. We show that phone discrimination is correlated with several types of models, and give recommendations for researchers seeking easily calculated norms of acoustic distance on experimental stimuli. We show that DeepSpeech, a standard English speech recognizer, is more specialized on English phoneme discrimination than English listeners, and is poorly correlated with their behaviour, even though it yields a low error on the decision task given to humans.
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Keyword:
[INFO]Computer Science [cs]; [SCCO]Cognitive science; Acoustic distance; Benchmarks; Speech perception; Speech recognition
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URL: https://hal.archives-ouvertes.fr/hal-03087248/file/Cog_Sci_2020___Predicting_phoneme_confusions__Juliette_.pdf
https://hal.archives-ouvertes.fr/hal-03087248/document
https://hal.archives-ouvertes.fr/hal-03087248
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Perceptimatic: A human speech perception benchmark for unsupervised subword modelling
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In: Interspeech 2020 - 21st Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03087252 ; Interspeech 2020 - 21st Annual Conference of the International Speech Communication Association, Oct 2020, Shanghai / Virtual, China ; http://www.interspeech2020.org/ (2020)
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Modelling Perceptual Effects of Phonology with ASR Systems
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In: CogSci 2020 - 42nd Annual Virtual Meeting of the Cognitive Science Society ; https://hal.archives-ouvertes.fr/hal-03070281 ; CogSci 2020 - 42nd Annual Virtual Meeting of the Cognitive Science Society, Jul 2020, Virtual, France (2020)
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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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Analogies minus analogy test: measuring regularities in word embeddings
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In: CoNLL 2020 - 24th Conference on Computational Natural Language Learning ; https://hal.archives-ouvertes.fr/hal-03070260 ; CoNLL 2020 - 24th Conference on Computational Natural Language Learning, Nov 2020, Virtual, France (2020)
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Independent and Automatic Evaluation of Speaker-Independent Acoustic-to-Articulatory Reconstruction
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In: Interspeech 2020 - 21st Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03087264 ; Interspeech 2020 - 21st Annual Conference of the International Speech Communication Association, Oct 2020, Shanghai / Virtual, China ; http://www.interspeech2020.org/ (2020)
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Analogies minus analogy test: measuring regularities in word embeddings ...
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The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling ...
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Perceptimatic: A human speech perception benchmark for unsupervised subword modelling ...
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The Perceptimatic English Benchmark for Speech Perception Models ...
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Tensor Product Decomposition Networks: Uncovering Representations of Structure Learned by Neural Networks
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In: Proceedings of the Society for Computation in Linguistics (2020)
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Comparing unsupervised speech learning directly to human performance in speech perception
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In: Proceedings of the Annual Conference of the Cognitive Science Society (Cog Sci) ; CogSci 2019 - 41st Annual Meeting of Cognitive Science Society ; https://hal.archives-ouvertes.fr/hal-02274499 ; CogSci 2019 - 41st Annual Meeting of Cognitive Science Society, Jul 2019, Montréal, Canada (2019)
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Generative grammar, neural networks, and the implementational mapping problem: Response to Pater
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In: ISSN: 0097-8507 ; EISSN: 1535-0665 ; Language ; https://hal.archives-ouvertes.fr/hal-02274522 ; Language, Linguistic Society of America, 2019, 95 (1), pp.e87-e98. ⟨10.1353/lan.2019.0013⟩ (2019)
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RNNs Implicitly Implement Tensor Product Representations
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In: International Conference on Learning Representations ; ICLR 2019 - International Conference on Learning Representations ; https://hal.archives-ouvertes.fr/hal-02274498 ; ICLR 2019 - International Conference on Learning Representations, May 2019, New Orleans, United States (2019)
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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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