通过语言提示微调和帧级语言适配器增强多语言语音识别
Enhancing Multilingual Speech Recognition through Language Prompt Tuning and Frame-Level Language Adapter
AI总结：
本文针对多语言语音识别提出语言提示微调和帧级语言适配器两种参数高效方法，分别提升语言可配置与语言无关场景下的识别性能，并在七种语言上验证了显著效果。
摘要：
多语言智能助手（如ChatGPT）近年来日益普及。为了进一步拓展多语言人工智能助手的应用并促进国际交流，提升多语言语音识别性能至关重要，它是语音交互的关键组成部分。本文提出两种简单且参数高效的方法：语言提示微调和帧级语言适配器，分别用于增强语言可配置和语言无关的多语言语音识别。此外，我们探索了利用参数高效微调方法整合这两种方案的可行性。实验表明，所提方法在七种语言上均取得了显著的性能提升。
英文摘要：
Multilingual intelligent assistants, such as ChatGPT, have recently gained popularity. To further expand the applications of multilingual artificial intelligence assistants and facilitate international communication, it is essential to enhance the performance of multilingual speech recognition, which is a crucial component of speech interaction. In this paper, we propose two simple and parameter-efficient methods: language prompt tuning and frame-level language adapter, to respectively enhance language-configurable and language-agnostic multilingual speech recognition. Additionally, we explore the feasibility of integrating these two approaches using parameter-efficient fine-tuning methods. Our experiments demonstrate significant performance improvements across seven languages using our proposed methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
