6 citations · 16 across the 19 of their papers we have counts for
4 papers · 1 filter
Improving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies
Zehan Li, Haoran Miao, Keqi Deng +4
There is often a trade-off between performance and latency in streaming automatic speech recognition (ASR). Traditional methods such as look-ahead and chunk-based methods, usually…
Blockwise Streaming Transformer for Spoken Language Understanding and Simultaneous Speech Translation
Keqi Deng, Shinji Watanabe, Jiatong Shi +1
Although Transformers have gained success in several speech processing tasks like spoken language understanding (SLU) and speech translation (ST), achieving online processing while…
Improving CTC-based speech recognition via knowledge transferring from pre-trained language models
Keqi Deng, Songjun Cao, Yike Zhang +4
Recently, end-to-end automatic speech recognition models based on connectionist temporal classification (CTC) have achieved impressive results, especially when fine-tuned from wav2…
Improving non-autoregressive end-to-end speech recognition with pre-trained acoustic and language models
Keqi Deng, Zehui Yang, Shinji Watanabe +3
While Transformers have achieved promising results in end-to-end (E2E) automatic speech recognition (ASR), their autoregressive (AR) structure becomes a bottleneck for speeding up…