LLaSM: Large Language and Speech Model

Yu Shu, Siwei Dong, Guangyao Chen, Wenhao Huang, Ruihua Zhang +3 more
8/30/2023
cs.CLcs.LGcs.SD

Official code: LinkSoul-AI/LLaSM (561 stars, Apache-2.0, last commit 2023-09-11).

Abstract

Multi-modal large language models have garnered significant interest recently. Though, most of the works focus on vision-language multi-modal models providing strong capabilities in following vision-and-language instructions. However, we claim that speech is also an important modality through which humans interact with the world. Hence, it is crucial for a general-purpose assistant to be able to follow multi-modal speech-and-language instructions. In this work, we propose Large Language and Speech Model (LLaSM). LLaSM is an end-to-end trained large multi-modal speech-language model with cross-modal conversational abilities, capable of following speech-and-language instructions. Our early experiments show that LLaSM demonstrates a more convenient and natural way for humans to interact with artificial intelligence. Specifically, we also release a large Speech Instruction Following dataset LLaSM-Audio-Instructions. Code and demo are available at https://github.com/LinkSoul-AI/LLaSM and https://huggingface.co/spaces/LinkSoul/LLaSM. The LLaSM-Audio-Instructions dataset is available at https://huggingface.co/datasets/LinkSoul/LLaSM-Audio-Instructions.

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Code Implementations(1)

LinkSoul-AI/LLaSMOfficial100%
Apache-2.0

第一个支持中英文双语语音-文本多模态对话的开源可商用对话模型。便捷的语音输入将大幅改善以文本为输入的大模型的使用体验,同时避免了基于 ASR 解决方案的繁琐流程以及可能引入的错误。

56153PythonJul 31, 20233 years agoApache-2.0

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Cite this paper

@article{shu2023llasm,
  title  = {LLaSM: Large Language and Speech Model},
  author = {Yu Shu and Siwei Dong and Guangyao Chen and Wenhao Huang and Ruihua Zhang and Daochen Shi and Qiqi Xiang and Yemin Shi},
  year   = {2023},
  eprint = {2308.15930},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.15930v3}
}

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