SimulSeamless: FBK at IWSLT 2024 Simultaneous Speech Translation
원문 초록
This paper describes the FBK's participation in the Simultaneous Translation Evaluation Campaign at IWSLT 2024. For this year's submission in the speech-to-text translation (ST) sub-track, we propose SimulSeamless, which is realized by combining AlignAtt and SeamlessM4T in its medium configuration. The SeamlessM4T model is used "off-the-shelf" and its simultaneous inference is enabled through the adoption of AlignAtt, a SimulST policy based on cross-attention that can be applied without any retraining or adaptation of the underlying model for the simultaneous task. We participated in all the Shared Task languages (English->{German, Japanese, Chinese}, and Czech->English), achieving acceptable or even better results compared to last year's submissions. SimulSeamless, covering more than 143 source languages and 200 target languages, is released at: https://github.com/hlt-mt/FBK-fairseq/.
함께 살펴볼 논문
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BeaverTalk: Oregon State University's IWSLT 2025 Simultaneous Speech Translation System
End-to-End Speech Translation for Low-Resource Languages Using Weakly Labeled Data
S2ST-Omni: An Efficient and Scalable Multilingual Speech-to-Speech Translation Framework via Seamless Speech-Text Alignment and Streaming Speech Generation
Improving Language and Modality Transfer in Translation by Character-level Modeling
Speech-to-Text Translation with Phoneme-Augmented CoT: Enhancing Cross-Lingual Transfer in Low-Resource Scenarios
AdaST: Dynamically Adapting Encoder States in the Decoder for End-to-End Speech-to-Text Translation
토론
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