低资源语音识别研究进展
Research Progress of Low-Resource Speech Recognition
余正涛 1董凌 1高盛祥1
作者信息
- 1. 昆明理工大学 信息工程与自动化学院,云南 昆明 650500;云南省人工智能重点实验室,云南 昆明 650500
- 折叠
摘要
探讨低资源语音识别领域最新研究进展,旨在为未来研究和应用提供有益参考.首先,简要回顾了语音识别的发展过程,并介绍了当前主流端到端语音识别框架的基本原理.其次,针对低资源语音识别面临的问题,详细分析了在语音数据增强、自监督语音表征学习、多语言联合学习、结合大语言模型以及语言知识增强5 个方面的相关研究工作.最后,对低资源语音识别未来的研究方向进行了展望.
Abstract
This paper explores the latest research advancements in low-resource speech recognition,aiming to provide valuable references for future research and applications.It first briefly reviews the development process of speech recognition and introduces the basic principles of the current mainstream end-to-end speech recogni-tion frameworks.Addressing the challenges faced in low-resource speech recognition,the paper provides a de-tailed analysis of related research in five areas:speech data augmentation,self-supervised speech representation learning,multilingual joint learning,integration of large language models,and enhancement of language knowl-edge.Finally,it outlines the future research directions of low-resource speech recognition.
关键词
语音识别/低资源语言/数据增强/语音表征学习/大语言模型/语言知识Key words
speech recognition/low-resource languages/data augmentation/speech representation learning/large language model/language knowledge引用本文复制引用
基金项目
国家自然科学基金项目(62376111)
国家自然科学基金项目(U23A20388)
云南省基础研究重大项目(202401BC070021)
云南省重点研发计划项目(202303AP140008)
出版年
2024
NETL
NSTL
万方数据