{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/cot-st-enhancing-llm-based-speech-translation","title":"CoT-ST: Enhancing LLM-based Speech Translation with Multimodal Chain-of-Thought","arxiv_id":"2409.19510","date":"2024-09-29","proceeding":null,"authors":["Yexing Du","Ziyang Ma","Yifan Yang","Keqi Deng","Xie Chen","Bo Yang","Yang Xiang","Ming Liu","Bing Qin"],"abstract":"Speech Language Models (SLMs) have demonstrated impressive performance on speech translation tasks. However, existing research primarily focuses on direct instruction fine-tuning and often overlooks the inherent reasoning capabilities of SLMs. In this paper, we introduce a three-stage training framework designed to activate the chain-of-thought (CoT) capabilities of SLMs. We propose CoT-ST, a speech translation model that utilizes multimodal CoT to decompose speech translation into sequential steps of speech recognition and translation. We validated the effectiveness of our method on two datasets: the CoVoST-2 dataset and MuST-C dataset. The experimental results demonstrate that CoT-ST outperforms previous state-of-the-art methods, achieving higher BLEU scores (CoVoST-2 en-ja: 30.5->30.8, en-zh: 45.2->47.7, MuST-C en-zh: 19.6->21.2). This work is open sourced at https://github.com/X-LANCE/SLAM-LLM/tree/main/examples/st_covost2 .","url_abs":"https://arxiv.org/abs/2409.19510v1","url_pdf":"https://arxiv.org/pdf/2409.19510v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"cot-st-enhancing-llm-based-speech-translation","repo_url":"https://github.com/X-LANCE/SLAM-LLM","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"translation","task_name":"Translation"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2409.19510","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}