85 citations · 135 across the 18 of their papers we have counts for
11 papers · 1 filter
FSR: Accelerating the Inference Process of Transducer-Based Models by Applying Fast-Skip Regularization
Zhengkun Tian, Jiangyan Yi, Ye Bai +3
Transducer-based models, such as RNN-Transducer and transformer-transducer, have achieved great success in speech recognition. A typical transducer model decodes the output sequenc…
One In A Hundred: Select The Best Predicted Sequence from Numerous Candidates for Streaming Speech Recognition
Zhengkun Tian, Jiangyan Yi, Ye Bai +3
The RNN-Transducers and improved attention-based encoder-decoder models are widely applied to streaming speech recognition. Compared with these two end-to-end models, the CTC model…
Spike-Triggered Non-Autoregressive Transformer for End-to-End Speech Recognition
Zhengkun Tian, Jiangyan Yi, Jianhua Tao +3
Non-autoregressive transformer models have achieved extremely fast inference speed and comparable performance with autoregressive sequence-to-sequence models in neural machine tran…
Listen Attentively, and Spell Once: Whole Sentence Generation via a Non-Autoregressive Architecture for Low-Latency Speech Recognition
Ye Bai, Jiangyan Yi, Jianhua Tao +3
Although attention based end-to-end models have achieved promising performance in speech recognition, the multi-pass forward computation in beam-search increases inference time cos…
Simultaneous Denoising and Dereverberation Using Deep Embedding Features
Cunhang Fan, Jianhua Tao, Bin Liu +2
Monaural speech dereverberation is a very challenging task because no spatial cues can be used. When the additive noises exist, this task becomes more challenging. In this paper, w…
Deep Attention Fusion Feature for Speech Separation with End-to-End Post-filter Method
Cunhang Fan, Jianhua Tao, Bin Liu +3
In this paper, we propose an end-to-end post-filter method with deep attention fusion features for monaural speaker-independent speech separation. At first, a time-frequency domain…