67 citations · 588 across the 61 of their papers we have counts for
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End-to-End Monaural Multi-speaker ASR System without Pretraining
Xuankai Chang, Yanmin Qian, Kai Yu +1
Recently, end-to-end models have become a popular approach as an alternative to traditional hybrid models in automatic speech recognition (ASR). The multi-speaker speech separation…
Towards Universal Dialogue State Tracking
Liliang Ren, Kaige Xie, Lu Chen +1
Dialogue state tracking is the core part of a spoken dialogue system. It estimates the beliefs of possible user's goals at every dialogue turn. However, for most current approaches…
Sequence Discriminative Training for Deep Learning based Acoustic Keyword Spotting
Zhehuai Chen, Yanmin Qian, Kai Yu
Speech recognition is a sequence prediction problem. Besides employing various deep learning approaches for framelevel classification, sequence-level discriminative training has be…
Deep Discriminant Analysis for i-vector Based Robust Speaker Recognition
Shuai Wang, Zili Huang, Yanmin Qian +1
Linear Discriminant Analysis (LDA) has been used as a standard post-processing procedure in many state-of-the-art speaker recognition tasks. Through maximizing the inter-speaker di…
On Modular Training of Neural Acoustics-to-Word Model for LVCSR
Zhehuai Chen, Qi Liu, Hao Li +1
End-to-end (E2E) automatic speech recognition (ASR) systems directly map acoustics to words using a unified model. Previous works mostly focus on E2E training a single model which…