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Joint Modeling of Code-Switched and Monolingual ASR via Conditional Factorization ...
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Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation ...
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Self-Guided Curriculum Learning for Neural Machine Translation ...
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Arabic Speech Recognition by End-to-End, Modular Systems and Human ...
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Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yoloxóchitl Mixtec ...
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Leveraging Pre-trained Language Model for Speech Sentiment Analysis ...
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Differentiable Allophone Graphs for Language-Universal Speech Recognition ...
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Speech Representation Learning Combining Conformer CPC with Deep Cluster for the ZeroSpeech Challenge 2021 ...
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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. ...
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Keyword:
Audio and Speech Processing eess.AS; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD
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URL: https://dx.doi.org/10.48550/arxiv.2107.05899 https://arxiv.org/abs/2107.05899
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Towards Online End-to-end Transformer Automatic Speech Recognition ...
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Analysis of Multilingual Sequence-to-Sequence speech recognition systems ...
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Language model integration based on memory control for sequence to sequence speech recognition ...
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Transfer learning of language-independent end-to-end ASR with language model fusion ...
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Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling ...
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