62 citations · 655 across the 97 of their papers we have counts for
8 papers · 1 filter
Exploring RNN-Transducer for Chinese Speech Recognition
Senmao Wang, Pan Zhou, Wei Chen +2
End-to-end approaches have drawn much attention recently for significantly simplifying the construction of an automatic speech recognition (ASR) system. RNN transducer (RNN-T) is o…
Learning Acoustic Word Embeddings with Temporal Context for Query-by-Example Speech Search
Yougen Yuan, Cheung-Chi Leung, Lei Xie +3
We propose to learn acoustic word embeddings with temporal context for query-by-example (QbE) speech search. The temporal context includes the leading and trailing word sequences o…
Training Augmentation with Adversarial Examples for Robust Speech Recognition
Sining Sun, Ching-Feng Yeh, Mari Ostendorf +2
This paper explores the use of adversarial examples in training speech recognition systems to increase robustness of deep neural network acoustic models. During training, the fast…
Study of Semi-supervised Approaches to Improving English-Mandarin Code-Switching Speech Recognition
Pengcheng Guo, Haihua Xu, Lei Xie +1
In this paper, we present our overall efforts to improve the performance of a code-switching speech recognition system using semi-supervised training methods from lexicon learning…
Domain Adversarial Training for Accented Speech Recognition
Sining Sun, Ching-Feng Yeh, Mei-Yuh Hwang +2
In this paper, we propose a domain adversarial training (DAT) algorithm to alleviate the accented speech recognition problem. In order to reduce the mismatch between labeled source…
Attention-based End-to-End Models for Small-Footprint Keyword Spotting
Changhao Shan, Junbo Zhang, Yujun Wang +1
In this paper, we propose an attention-based end-to-end neural approach for small-footprint keyword spotting (KWS), which aims to simplify the pipelines of building a production-qu…
Empirical Evaluation of Speaker Adaptation on DNN based Acoustic Model
Ke Wang, Junbo Zhang, Yujun Wang +1
Speaker adaptation aims to estimate a speaker specific acoustic model from a speaker independent one to minimize the mismatch between the training and testing conditions arisen fro…
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition
Ke Wang, Junbo Zhang, Sining Sun +3
We investigate the use of generative adversarial networks (GANs) in speech dereverberation for robust speech recognition. GANs have been recently studied for speech enhancement to…