67 citations · 380 across the 51 of their papers we have counts for
7 papers · 1 filter
Convolutive Transfer Function Invariant SDR training criteria for Multi-Channel Reverberant Speech Separation
Christoph Boeddeker, Wangyou Zhang, Tomohiro Nakatani +6
Time-domain training criteria have proven to be very effective for the separation of single-channel non-reverberant speech mixtures. Likewise, mask-based beamforming has shown impr…
Data Augmentation for End-to-end Code-switching Speech Recognition
Chenpeng Du, Hao Li, Yizhou Lu +2
Training a code-switching end-to-end automatic speech recognition (ASR) model normally requires a large amount of data, while code-switching data is often limited. In this paper, t…
End-to-End Speaker-Dependent Voice Activity Detection
Yefei Chen, Shuai Wang, Yanmin Qian +1
Voice activity detection (VAD) is an essential pre-processing step for tasks such as automatic speech recognition (ASR) and speaker recognition. A basic goal is to remove silent se…
Future Vector Enhanced LSTM Language Model for LVCSR
Qi Liu, Yanmin Qian, Kai Yu
Language models (LM) play an important role in large vocabulary continuous speech recognition (LVCSR). However, traditional language models only predict next single word with given…
End-to-end spoofing detection with raw waveform CLDNNs
Heinrich Dinkel, Nanxin Chen, Yanmin Qian +1
Albeit recent progress in speaker verification generates powerful models, malicious attacks in the form of spoofed speech, are generally not coped with. Recent results in ASVSpoof2…
End-to-End Far-Field Speech Recognition with Unified Dereverberation and Beamforming
Wangyou Zhang, Aswin Shanmugam Subramanian, Xuankai Chang +2
Despite successful applications of end-to-end approaches in multi-channel speech recognition, the performance still degrades severely when the speech is corrupted by reverberation.…
End-to-End Multi-speaker Speech Recognition with Transformer
Xuankai Chang, Wangyou Zhang, Yanmin Qian +2
Recently, fully recurrent neural network (RNN) based end-to-end models have been proven to be effective for multi-speaker speech recognition in both the single-channel and multi-ch…