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eess.AS2022
An Empirical Study of Language Model Integration for Transducer based Speech Recognition
Huahuan Zheng, Keyu An, Zhijian Ou +3
Utilizing text-only data with an external language model (ELM) in end-to-end RNN-Transducer (RNN-T) for speech recognition is challenging. Recently, a class of methods such as dens…
eess.AS2022
CUSIDE: Chunking, Simulating Future Context and Decoding for Streaming ASR
Keyu An, Huahuan Zheng, Zhijian Ou +3
History and future contextual information are known to be important for accurate acoustic modeling. However, acquiring future context brings latency for streaming ASR. In this pape…
eess.AS2022
Exploiting Single-Channel Speech for Multi-Channel End-to-End Speech Recognition: A Comparative Study
Keyu An, Ji Xiao, Zhijian Ou
Recently, the end-to-end training approach for multi-channel ASR has shown its effectiveness, which usually consists of a beamforming front-end and a recognition back-end. However,…