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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 Page: 1 2 Hits 1 – 20 of 21 1 Measuring the Impact of Individual Domain Factors in Self-Supervised Pre-Training ... Sanabria, Ramon; Hsu, Wei-Ning; Baevski, Alexei; Auli, Michael. - : arXiv, 2022 Abstract: Human speech data comprises a rich set of domain factors such as accent, syntactic and semantic variety, or acoustic environment. Previous work explores the effect of domain mismatch in automatic speech recognition between pre-training and fine-tuning as a whole but does not dissect the contribution of individual factors. In this paper, we present a controlled study to better understand the effect of such factors on the performance of pre-trained representations. To do so, we pre-train models either on modified natural speech or synthesized audio, with a single domain factor modified, and then measure performance on automatic speech recognition after fine tuning. Results show that phonetic domain factors play an important role during pre-training while grammatical and syntactic factors are far less important. To our knowledge, this is the first study to better understand the domain characteristics in self-supervised pre-training for speech. ... : Submitted to Insterspeech 2022 ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://arxiv.org/abs/2203.00648 https://dx.doi.org/10.48550/arxiv.2203.00648 BASE Hide details 2 Simple and Effective Unsupervised Speech Synthesis ... Liu, Alexander H.; Lai, Cheng-I Jeff; Hsu, Wei-Ning. - : arXiv, 2022 BASE Show details 3 Speech Resynthesis from Discrete Disentangled Self-Supervised Representations Polyak, Adam; Adi, Yossi; Copet, Jade... In: INTERSPEECH 2021 - Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-03329245 ; INTERSPEECH 2021 - Annual Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021) BASE Show details 4 On Generative Spoken Language Modeling from Raw Audio Lakhotia, Kushal; Kharitonov, Evgeny; Hsu, Wei-Ning... In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03329219 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021 (2021) BASE Show details 5 Generative Spoken Language Modeling from Raw Audio ... Lakhotia, Kushal; Kharitonov, Evgeny; Hsu, Wei-Ning. - : arXiv, 2021 BASE Show details 6 Text-Free Image-to-Speech Synthesis Using Learned Segmental Units ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Glass, James; Harwath, David. - : Underline Science Inc., 2021 BASE Show details 7 Generative Spoken Language Modeling from Raw Audio ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Adi, Yossi; Baevski, Alexei. - : Underline Science Inc., 2021 BASE Show details 8 Textless Speech-to-Speech Translation on Real Data ... Lee, Ann; Gong, Hongyu; Duquenne, Paul-Ambroise. - : arXiv, 2021 BASE Show details 9 HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units ... Hsu, Wei-Ning; Bolte, Benjamin; Tsai, Yao-Hung Hubert. - : arXiv, 2021 BASE Show details 10 Textless Speech Emotion Conversion using Discrete and Decomposed Representations ... Kreuk, Felix; Polyak, Adam; Copet, Jade. - : arXiv, 2021 BASE Show details 11 A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning Khurana, Sameer; Laurent, Antoine; Hsu, Wei-Ning... In: Interspeech 2020 ; https://hal.archives-ouvertes.fr/hal-02912029 ; Interspeech 2020, Oct 2020, Shanghai, China (2020) BASE Show details 12 Speech processing with less supervision : learning from weak labels and multiple modalities Hsu, Wei-Ning,Ph. D.Massachusetts Institute of Technology.. - : Massachusetts Institute of Technology, 2020 BASE Show details 13 A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning ... Khurana, Sameer; Laurent, Antoine; Hsu, Wei-Ning. - : arXiv, 2020 BASE Show details 14 Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech ... Harwath, David; Hsu, Wei-Ning; Glass, James. - : arXiv, 2019 BASE Show details 15 Transfer Learning from Audio-Visual Grounding to Speech Recognition ... Hsu, Wei-Ning; Harwath, David; Glass, James. - : arXiv, 2019 BASE Show details 16 Unsupervised learning of disentangled representations for speech with neural variational inference models Hsu, Wei-Ning, Ph. D. Massachusetts Institute of Technology. - : Massachusetts Institute of Technology, 2018 BASE Show details 17 Unsupervised Adaptation with Interpretable Disentangled Representations for Distant Conversational Speech Recognition ... Hsu, Wei-Ning; Tang, Hao; Glass, James. - : arXiv, 2018 BASE Show details 18 Unsupervised Representation Learning of Speech for Dialect Identification ... Shon, Suwon; Hsu, Wei-Ning; Glass, James. - : arXiv, 2018 BASE Show details 19 Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data ... Hsu, Wei-Ning; Zhang, Yu; Glass, James. - : arXiv, 2017 BASE Show details 20 Learning Latent Representations for Speech Generation and Transformation ... Hsu, Wei-Ning; Zhang, Yu; Glass, James. - : arXiv, 2017 BASE Show details Page: 1 2

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