Leveraging Pseudo-labeled Data to Improve Direct Speech-to-Speech Translation
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Abstract (arXiv)
Direct Speech-to-speech translation (S2ST) has drawn more and more attention recently. The task is very challenging due to data scarcity and complex speech-to-speech mapping. In this paper, we report our recent achievements in S2ST. Firstly, we build a S2ST Transformer baseline which outperforms the original Translatotron. Secondly, we utilize the external data by pseudo-labeling and obtain a new state-of-the-art result on the Fisher English-to-Spanish test set. Indeed, we exploit the pseudo data with a combination of popular techniques which are not trivial when applied to S2ST. Moreover, we evaluate our approach on both syntactically similar (Spanish-English) and distant (English-Chinese) language pairs. Our implementation is available at https://github.com/fengpeng-yue/speech-to-speech-translation.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 21 of its 28 references that are in the map. First posted on arXiv 18 May 2022.
Builds on
21 of 28 references.
References · 21
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9 more
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Built on by
Citing papers per year: 2022: 6; 2023: 6.
12 papers.
- 2022UnitY: Two-pass Direct Speech-to-speech Translation with Discrete Unitscited by 60
- 2022Speech-to-Speech Translation For A Real-world Unwritten Languagecited by 25
- 2022Textless Direct Speech-to-Speech Translation with Discrete Speech Representationcited by 19
- 2023PolyVoice: Language Models for Speech to Speech Translationcited by 19
- 2023MixSpeech: Cross-Modality Self-Learning with Audio-Visual Stream Mixup for Visual Speech Translation and Recognitioncited by 14
- 2023Translatotron 3: Speech to Speech Translation with Monolingual Datacited by 12
- 2022Joint Pre-Training with Speech and Bilingual Text for Direct Speech to Speech Translationcited by 9
- 2023DASpeech: Directed Acyclic Transformer for Fast and High-quality Speech-to-Speech Translationcited by 9
- 2023Towards cross-language prosody transfer for dialogcited by 5
- 2022Joint Speech Transcription and Translation: Pseudo-Labeling with Out-of-Distribution Datacited by 3
- 2022Direct Speech-to-speech Translation without Textual Annotation using Bottleneck Featurescited by 1
- 2023Listen to Minority: Encrypted Traffic Classification for Class Imbalance with Contrastive Pre-Trainingcited by 1
- 2023DASpeech: Directed Acyclic Transformer for Fast and High-quality Speech-to-Speech Translation11 Oct 2023
- 2023Listen to Minority: Encrypted Traffic Classification for Class Imbalance with Contrastive Pre-Training31 Aug 2023
- 2023Towards cross-language prosody transfer for dialog9 Jul 2023
- 2023PolyVoice: Language Models for Speech to Speech Translation5 Jun 2023
- 2023Translatotron 3: Speech to Speech Translation with Monolingual Data27 May 2023
- 2023MixSpeech: Cross-Modality Self-Learning with Audio-Visual Stream Mixup for Visual Speech Translation and Recognition9 Mar 2023
- 2022Joint Speech Transcription and Translation: Pseudo-Labeling with Out-of-Distribution Data20 Dec 2022
- 2022UnitY: Two-pass Direct Speech-to-speech Translation with Discrete Units15 Dec 2022
- 2022Direct Speech-to-speech Translation without Textual Annotation using Bottleneck Features12 Dec 2022
- 2022Speech-to-Speech Translation For A Real-world Unwritten Language11 Nov 2022
- 2022Textless Direct Speech-to-Speech Translation with Discrete Speech Representation31 Oct 2022
- 2022Joint Pre-Training with Speech and Bilingual Text for Direct Speech to Speech Translation31 Oct 2022