9 citations · 35 across the 7 of their papers we have counts for
3 papers · 1 filter
Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition
Kenichi Kumatani, Robert Gmyr, Felipe Cruz Salinas +5
The sparsely-gated Mixture of Experts (MoE) can magnify a network capacity with a little computational complexity. In this work, we investigate how multi-lingual Automatic Speech R…
Multilingual Speech Recognition using Knowledge Transfer across Learning Processes
Rimita Lahiri, Kenichi Kumatani, Eric Sun +1
Multilingual end-to-end(E2E) models have shown a great potential in the expansion of the language coverage in the realm of automatic speech recognition(ASR). In this paper, we aim…
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian +5
In this paper, we propose a unified pre-training approach called UniSpeech to learn speech representations with both unlabeled and labeled data, in which supervised phonetic CTC le…