5 citations · 10 across the 11 of their papers we have counts for
14 papers
Massively Multilingual ASR on 70 Languages: Tokenization, Architecture, and Generalization Capabilities
Andros Tjandra, Nayan Singhal, David Zhang +4
End-to-end multilingual ASR has become more appealing because of several reasons such as simplifying the training and deployment process and positive performance transfer from high…
Joint Audio/Text Training for Transformer Rescorer of Streaming Speech Recognition
Suyoun Kim, Ke Li, Lucas Kabela +4
Recently, there has been an increasing interest in two-pass streaming end-to-end speech recognition (ASR) that incorporates a 2nd-pass rescoring model on top of the conventional 1s…
Federated Domain Adaptation for ASR with Full Self-Supervision
Junteng Jia, Jay Mahadeokar, Weiyi Zheng +3
Cross-device federated learning (FL) protects user privacy by collaboratively training a model on user devices, therefore eliminating the need for collecting, storing, and manually…
Streaming parallel transducer beam search with fast-slow cascaded encoders
Jay Mahadeokar, Yangyang Shi, Ke Li +5
Streaming ASR with strict latency constraints is required in many speech recognition applications. In order to achieve the required latency, streaming ASR models sacrifice accuracy…
Neural-FST Class Language Model for End-to-End Speech Recognition
Antoine Bruguier, Duc Le, Rohit Prabhavalkar +7
We propose Neural-FST Class Language Model (NFCLM) for end-to-end speech recognition, a novel method that combines neural network language models (NNLMs) and finite state transduce…
Streaming Transformer Transducer Based Speech Recognition Using Non-Causal Convolution
Yangyang Shi, Chunyang Wu, Dilin Wang +9
This paper improves the streaming transformer transducer for speech recognition by using non-causal convolution. Many works apply the causal convolution to improve streaming transf…