Improving Stability in Simultaneous Speech Translation: A Revision-Controllable Decoding Approach
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Abstract (arXiv)
Simultaneous Speech-to-Text translation serves a critical role in real-time crosslingual communication. Despite the advancements in recent years, challenges remain in achieving stability in the translation process, a concern primarily manifested in the flickering of partial results. In this paper, we propose a novel revision-controllable method designed to address this issue. Our method introduces an allowed revision window within the beam search pruning process to screen out candidate translations likely to cause extensive revisions, leading to a substantial reduction in flickering and, crucially, providing the capability to completely eliminate flickering. The experiments demonstrate the proposed method can significantly improve the decoding stability without compromising substantially on the translation quality.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 14 of its 29 references that are in the map. First posted on arXiv 6 Oct 2023.
Builds on
14 of 29 references.
References · 14
- 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
- 2020Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Losscited by 235
- 2020Developing Real-time Streaming Transformer Transducer for Speech Recognition on Large-scale Datasetcited by 97
- 2019Transformer-Transducer: End-to-End Speech Recognition with Self-Attentioncited by 69
- 2021Direct Simultaneous Speech-to-Text Translation Assisted by Synchronized Streaming ASRcited by 31
- 2022Large-Scale Streaming End-to-End Speech Translation with Neural Transducerscited by 31
- 2019Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translationcited by 30
- 2019Re-Translation Strategies For Long Form, Simultaneous, Spoken Language Translationcited by 25
- 2020Improving Simultaneous Translation by Incorporating Pseudo-References with Fewer Reorderingscited by 20
- 2023Hybrid Transducer and Attention based Encoder-Decoder Modeling for Speech-to-Text Taskscited by 20
- 2022A Weakly-Supervised Streaming Multilingual Speech Model with Truly Zero-Shot Capabilitycited by 12
- 2019Speculative Beam Search for Simultaneous Translationcited by 10
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2 papers.