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MoLE : Mixture of Language Experts for Multi-Lingual Automatic Speech Recognition
- Publication Year :
- 2023
-
Abstract
- Multi-lingual speech recognition aims to distinguish linguistic expressions in different languages and integrate acoustic processing simultaneously. In contrast, current multi-lingual speech recognition research follows a language-aware paradigm, mainly targeted to improve recognition performance rather than discriminate language characteristics. In this paper, we present a multi-lingual speech recognition network named Mixture-of-Language-Expert(MoLE), which digests speech in a variety of languages. Specifically, MoLE analyzes linguistic expression from input speech in arbitrary languages, activating a language-specific expert with a lightweight language tokenizer. The tokenizer not only activates experts, but also estimates the reliability of the activation. Based on the reliability, the activated expert and the language-agnostic expert are aggregated to represent language-conditioned embedding for efficient speech recognition. Our proposed model is evaluated in 5 languages scenario, and the experimental results show that our structure is advantageous on multi-lingual recognition, especially for speech in low-resource language.<br />Comment: Accepted by ICASSP 2023
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2302.13750
- Document Type :
- Working Paper