MoLE : Mixture Of Language Experts For Multi-Lingual Automatic Speech Recognition
Author:
Affiliation:
1. NAVER Cloud,South Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10094559/10094560/10096227.pdf?arnumber=10096227
Reference26 articles.
1. Adaptand-adjust: Overcoming the long-tail problem of multilingual speech recognition;winata;InterSpeech,2021
2. Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model
3. Meta Learning for End-To-End Low-Resource Speech Recognition
4. Meta-adapter: Efficient cross-lingual adaptation with metalearning;hou;ICASSP,2021
5. Multi-task Learning of Deep Neural Networks for Low-resource Speech Recognition
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. LAE-ST-MOE: Boosted Language-Aware Encoder Using Speech Translation Auxiliary Task for E2E Code-Switching ASR;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16
2. Human-technology integration with industrial conversational agents: A conceptual architecture and a taxonomy for manufacturing;Journal of Industrial Information Integration;2023-10
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