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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 14 of 14 1 Pseudo-Labeling for Massively Multilingual Speech Recognition ... Lugosch, Loren; Likhomanenko, Tatiana; Synnaeve, Gabriel. - : arXiv, 2021 BASE Show details 2 LIBRI-LIGHT: a benchmark for asr with limited or no supervision Kahn, Jacob; Rivière, Morgane; Zheng, Weiyi... 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) BASE Show details 3 Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters ... Pratap, Vineel; Sriram, Anuroop; Tomasello, Paden. - : arXiv, 2020 BASE Show details 4 MLS: A Large-Scale Multilingual Dataset for Speech Research ... Pratap, Vineel; Xu, Qiantong; Sriram, Anuroop. - : arXiv, 2020 BASE Show details 5 Unsupervised Cross-lingual Representation Learning for Speech Recognition ... Conneau, Alexis; Baevski, Alexei; Collobert, Ronan; Mohamed, Abdelrahman; Auli, Michael. - : arXiv, 2020 Abstract: This paper presents XLSR which learns cross-lingual speech representations by pretraining a single model from the raw waveform of speech in multiple languages. We build on wav2vec 2.0 which is trained by solving a contrastive task over masked latent speech representations and jointly learns a quantization of the latents shared across languages. The resulting model is fine-tuned on labeled data and experiments show that cross-lingual pretraining significantly outperforms monolingual pretraining. On the CommonVoice benchmark, XLSR shows a relative phoneme error rate reduction of 72% compared to the best known results. On BABEL, our approach improves word error rate by 16% relative compared to a comparable system. Our approach enables a single multilingual speech recognition model which is competitive to strong individual models. Analysis shows that the latent discrete speech representations are shared across languages with increased sharing for related languages. We hope to catalyze research in low-resource ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG; Sound cs.SD URL: https://arxiv.org/abs/2006.13979 https://dx.doi.org/10.48550/arxiv.2006.13979 BASE Hide details 6 End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition Collobert, Ronan; Magimai.-Doss, Mathew; Palaz, Dimitri In: http://infoscience.epfl.ch/record/264125 (2019) BASE Show details 7 End-to-End Speech Recognition From the Raw Waveform Zeghidour, Neil; Usunier, Nicolas; Synnaeve, Gabriel... In: Interspeech 2018 ; https://hal.archives-ouvertes.fr/hal-01888739 ; Interspeech 2018, Sep 2018, Hyderabad, India. ⟨10.21437/Interspeech.2018-2414⟩ (2018) BASE Show details 8 Fully Convolutional Speech Recognition ... Zeghidour, Neil; Xu, Qiantong; Liptchinsky, Vitaliy. - : arXiv, 2018 BASE Show details 9 Learning linearly separable features for speech recognition using convolutional neural networks ... Palaz, Dimitri; Doss, Mathew Magimai; Collobert, Ronan. - : arXiv, 2014 BASE Show details 10 Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks Magimai.-Doss, Mathew; Collobert, Ronan; Palaz, Dimitri In: http://infoscience.epfl.ch/record/192756 (2013) BASE Show details 11 Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks Palaz, Dimitri; Magimai.-Doss, Mathew; Collobert, Ronan In: http://infoscience.epfl.ch/record/192560 (2013) BASE Show details 12 Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks ... Palaz, Dimitri; Collobert, Ronan; -Doss, Mathew Magimai.. - : arXiv, 2013 BASE Show details 13 Towards Understanding Situated Natural Language Bordes, Antoine; Usunier, Nicolas; Collobert, Ronan... In: 13th International Conference on Artificial Intelligence and Statistics ; https://hal.archives-ouvertes.fr/hal-00750937 ; 13th International Conference on Artificial Intelligence and Statistics, May 2010, Chia Laguna Resort, Sardinia, Italy. pp.65-72 (2010) BASE Show details 14 Large Scale Application of Neural Network Based Semantic Role Labeling for Automated Relation Extraction from Biomedical Texts Barnickel, Thorsten; Weston, Jason; Collobert, Ronan. - : Public Library of Science, 2009 BASE Show details

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