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Given the great success of large language models (LLMs) across various tasks, in this paper, we introduce LLM-ST, a novel and effective speech translation model constructed upon a pre-trained LLM.
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B. Zhang, I. Titov, B. Haddow, and R. Sennrich, “Beyond sentence-level end-to-end speech translation: Context helps,” in Proc. of ACL , 2021, pp. 2566–2578
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A. B. Sai, A. K. Mohankumar, and M. M. Khapra, “A survey of evaluation metrics used for nlg systems,” ACM Computing Surveys (CSUR) , vol. 55, no. 2, pp. 1–39, 2022
2022
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A. Radford, J. W. Kim, T. Xu, G. Brockman, C. McLeavey, and I. Sutskever, “Robust speech recognition via large-scale weak supervision,” in Proc. ICML . PMLR, 2023, pp. 28 492–28 518
2023
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R. Ye, C. Zhao, T. Ko, C. Meng, T. Wang, M. Wang, and J. Cao, “Gigast: A 10,000-hour pseudo speech translation corpus,” in Proc. InterSpeech , 2023
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