55 citations · 82 across the 8 of their papers we have counts for
9 papers
Towards Decoupling Frontend Enhancement and Backend Recognition in Monaural Robust ASR
Yufeng Yang, Ashutosh Pandey, DeLiang Wang
It has been shown that the intelligibility of noisy speech can be improved by speech enhancement (SE) algorithms. However, monaural SE has not been established as an effective fron…
Time-Domain Speech Enhancement for Robust Automatic Speech Recognition
Yufeng Yang, Ashutosh Pandey, DeLiang Wang
It has been shown that the intelligibility of noisy speech can be improved by speech enhancement algorithms. However, speech enhancement has not been established as an effective fr…
Time-domain Ad-hoc Array Speech Enhancement Using a Triple-path Network
Ashutosh Pandey, Buye Xu, Anurag Kumar +3
Deep neural networks (DNNs) are very effective for multichannel speech enhancement with fixed array geometries. However, it is not trivial to use DNNs for ad-hoc arrays with unknow…
TPARN: Triple-path Attentive Recurrent Network for Time-domain Multichannel Speech Enhancement
Ashutosh Pandey, Buye Xu, Anurag Kumar +3
In this work, we propose a new model called triple-path attentive recurrent network (TPARN) for multichannel speech enhancement in the time domain. TPARN extends a single-channel d…
Self-attending RNN for Speech Enhancement to Improve Cross-corpus Generalization
Ashutosh Pandey, DeLiang Wang
Deep neural networks (DNNs) represent the mainstream methodology for supervised speech enhancement, primarily due to their capability to model complex functions using hierarchical…
Dual Application of Speech Enhancement for Automatic Speech Recognition
Ashutosh Pandey, Chunxi Liu, Yun Wang +1
In this work, we exploit speech enhancement for improving a recurrent neural network transducer (RNN-T) based ASR system. We employ a dense convolutional recurrent network (DCRN) f…
Dual-path Self-Attention RNN for Real-Time Speech Enhancement
Ashutosh Pandey, DeLiang Wang
We propose a dual-path self-attention recurrent neural network (DP-SARNN) for time-domain speech enhancement. We improve dual-path RNN (DP-RNN) by augmenting inter-chunk and intra-…
Dense CNN with Self-Attention for Time-Domain Speech Enhancement
Ashutosh Pandey, DeLiang Wang
Speech enhancement in the time domain is becoming increasingly popular in recent years, due to its capability to jointly enhance both the magnitude and the phase of speech. In this…
On Cross-Corpus Generalization of Deep Learning Based Speech Enhancement
Ashutosh Pandey, DeLiang Wang
In recent years, supervised approaches using deep neural networks (DNNs) have become the mainstream for speech enhancement. It has been established that DNNs generalize well to unt…