1.9k citations · 3.5k across the 108 of their papers we have counts for
6 papers · 1 filter
Acoustic-To-Word Model Without OOV
Jinyu Li, Guoli Ye, Rui Zhao +2
Recently, the acoustic-to-word model based on the Connectionist Temporal Classification (CTC) criterion was shown as a natural end-to-end model directly targeting words as output u…
Unsupervised Adaptation with Domain Separation Networks for Robust Speech Recognition
Zhong Meng, Zhuo Chen, Vadim Mazalov +2
Unsupervised domain adaptation of speech signal aims at adapting a well-trained source-domain acoustic model to the unlabeled data from target domain. This can be achieved by adver…
Improved training for online end-to-end speech recognition systems
Suyoun Kim, Michael L. Seltzer, Jinyu Li +1
Achieving high accuracy with end-to-end speech recognizers requires careful parameter initialization prior to training. Otherwise, the networks may fail to find a good local optimu…
Large-Scale Domain Adaptation via Teacher-Student Learning
Jinyu Li, Michael L. Seltzer, Xi Wang +2
High accuracy speech recognition requires a large amount of transcribed data for supervised training. In the absence of such data, domain adaptation of a well-trained acoustic mode…
Progressive Joint Modeling in Unsupervised Single-channel Overlapped Speech Recognition
Zhehuai Chen, Jasha Droppo, Jinyu Li +1
Unsupervised single-channel overlapped speech recognition is one of the hardest problems in automatic speech recognition (ASR). Permutation invariant training (PIT) is a state of t…
End-to-End Attention based Text-Dependent Speaker Verification
Shi-Xiong Zhang, Zhuo Chen, Yong Zhao +2
A new type of End-to-End system for text-dependent speaker verification is presented in this paper. Previously, using the phonetically discriminative/speaker discriminative DNNs as…