71 citations · 163 across the 26 of their papers we have counts for
11 papers · 1 filter
End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system
Zhengyi Zhang, Pan Zhou
End-to-end (E2E) speech recognition architectures assemble all components of traditional speech recognition system into a single model. Although it simplifies ASR system, it introd…
Wav-BERT: Cooperative Acoustic and Linguistic Representation Learning for Low-Resource Speech Recognition
Guolin Zheng, Yubei Xiao, Ke Gong +3
Unifying acoustic and linguistic representation learning has become increasingly crucial to transfer the knowledge learned on the abundance of high-resource language data for low-r…
Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interaction
Wei Wei, Jiayi Liu, Xianling Mao +4
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge i…
Exploiting Global Contextual Information for Document-level Named Entity Recognition
Zanbo Wang, Wei Wei, Xianling Mao +4
Most existing named entity recognition (NER) approaches are based on sequence labeling models, which focus on capturing the local context dependencies. However, the way of taking o…
Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation
Shuai Lin, Pan Zhou, Xiaodan Liang +4
Human doctors with well-structured medical knowledge can diagnose a disease merely via a few conversations with patients about symptoms. In contrast, existing knowledge-grounded di…
Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition
Yubei Xiao, Ke Gong, Pan Zhou +3
Low-resource automatic speech recognition (ASR) is challenging, as the low-resource target language data cannot well train an ASR model. To solve this issue, meta-learning formulat…