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1
Joint Modeling of Code-Switched and Monolingual ASR via Conditional Factorization ...
Yan, Brian; Zhang, Chunlei; Yu, Meng. - : arXiv, 2021
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2
Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation ...
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3
Self-Guided Curriculum Learning for Neural Machine Translation ...
Zhou, Lei; Ding, Liang; Duh, Kevin. - : arXiv, 2021
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4
Arabic Speech Recognition by End-to-End, Modular Systems and Human ...
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5
Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yoloxóchitl Mixtec ...
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6
On Prosody Modeling for ASR+TTS based Voice Conversion ...
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7
Leveraging Pre-trained Language Model for Speech Sentiment Analysis ...
Shon, Suwon; Brusco, Pablo; Pan, Jing. - : arXiv, 2021
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8
End-to-end ASR to jointly predict transcriptions and linguistic annotations ...
NAACL 2021 2021; Fujita, Yuya; Omachi, Motoi. - : Underline Science Inc., 2021
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9
Differentiable Allophone Graphs for Language-Universal Speech Recognition ...
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10
Speech Representation Learning Combining Conformer CPC with Deep Cluster for the ZeroSpeech Challenge 2021 ...
Abstract: We present a system for the Zero Resource Speech Challenge 2021, which combines a Contrastive Predictive Coding (CPC) with deep cluster. In deep cluster, we first prepare pseudo-labels obtained by clustering the outputs of a CPC network with k-means. Then, we train an additional autoregressive model to classify the previously obtained pseudo-labels in a supervised manner. Phoneme discriminative representation is achieved by executing the second-round clustering with the outputs of the final layer of the autoregressive model. We show that replacing a Transformer layer with a Conformer layer leads to a further gain in a lexical metric. Experimental results show that a relative improvement of 35% in a phonetic metric, 1.5% in the lexical metric, and 2.3% in a syntactic metric are achieved compared to a baseline method of CPC-small which is trained on LibriSpeech 460h data. We achieve top results in this challenge with the syntactic metric. ...
Keyword: Audio and Speech Processing eess.AS; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD
URL: https://dx.doi.org/10.48550/arxiv.2107.05899
https://arxiv.org/abs/2107.05899
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11
CHiME-6 Challenge: Tackling multispeaker speech recognition for unsegmented recordings
In: CHiME 2020 - 6th International Workshop on Speech Processing in Everyday Environments ; https://hal.inria.fr/hal-02546993 ; CHiME 2020 - 6th International Workshop on Speech Processing in Everyday Environments, May 2020, Barcelona / Virtual, Spain (2020)
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12
Learning Speaker Embedding from Text-to-Speech ...
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13
Massively Multilingual Adversarial Speech Recognition ...
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14
A Comparative Study on Transformer vs RNN in Speech Applications ...
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15
Multilingual End-to-End Speech Translation ...
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16
Towards Online End-to-end Transformer Automatic Speech Recognition ...
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17
Transformer ASR with Contextual Block Processing ...
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18
The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines
In: Interspeech 2018 - 19th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-01744021 ; Interspeech 2018 - 19th Annual Conference of the International Speech Communication Association, Sep 2018, Hyderabad, India (2018)
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19
Analysis of Multilingual Sequence-to-Sequence speech recognition systems ...
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20
Language model integration based on memory control for sequence to sequence speech recognition ...
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