34 citations · 195 across the 59 of their papers we have counts for
7 papers · 2 filters
Direct Speech-to-speech Translation without Textual Annotation using Bottleneck Features
Junhui Zhang, Junjie Pan, Xiang Yin +1
Speech-to-speech translation directly translates a speech utterance to another between different languages, and has great potential in tasks such as simultaneous interpretation. St…
BiFSMNv2: Pushing Binary Neural Networks for Keyword Spotting to Real-Network Performance
Haotong Qin, Xudong Ma, Yifu Ding +6
Deep neural networks, such as the Deep-FSMN, have been widely studied for keyword spotting (KWS) applications while suffering expensive computation and storage. Therefore, network…
Internal Language Model Estimation based Adaptive Language Model Fusion for Domain Adaptation
Rao Ma, Xiaobo Wu, Jin Qiu +4
ASR model deployment environment is ever-changing, and the incoming speech can be switched across different domains during a session. This brings a challenge for effective domain a…
A Novel Chinese Dialect TTS Frontend with Non-Autoregressive Neural Machine Translation
Junhui Zhang, Wudi Bao, Junjie Pan +2
Chinese dialects are different variations of Chinese and can be considered as different languages in the same language family with Mandarin. Though they all use Chinese characters,…
Improving Contextual Representation with Gloss Regularized Pre-training
Yu Lin, Zhecheng An, Peihao Wu +1
Though achieving impressive results on many NLP tasks, the BERT-like masked language models (MLM) encounter the discrepancy between pre-training and inference. In light of this gap…
Improving End-to-End Contextual Speech Recognition with Fine-Grained Contextual Knowledge Selection
Minglun Han, Linhao Dong, Zhenlin Liang +4
Nowadays, most methods in end-to-end contextual speech recognition bias the recognition process towards contextual knowledge. Since all-neural contextual biasing methods rely on ph…
BiFSMN: Binary Neural Network for Keyword Spotting
Haotong Qin, Xudong Ma, Yifu Ding +6
The deep neural networks, such as the Deep-FSMN, have been widely studied for keyword spotting (KWS) applications. However, computational resources for these networks are significa…