17 citations · 34 across the 4 of their papers we have counts for
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cs.CL2020★ 9 cited
Developing Real-time Streaming Transformer Transducer for Speech Recognition on Large-scale Dataset
Xie Chen, Yu Wu, Zhenghao Wang +2
Recently, Transformer based end-to-end models have achieved great success in many areas including speech recognition. However, compared to LSTM models, the heavy computational cost…
eess.AS2020★ 5 cited
Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability
Jinyu Li, Rui Zhao, Zhong Meng +8
Because of its streaming nature, recurrent neural network transducer (RNN-T) is a very promising end-to-end (E2E) model that may replace the popular hybrid model for automatic spee…