80 citations · 83 across the 7 of their papers we have counts for
7 papers
Teach an all-rounder with experts in different domains
Zhao You, Dan Su, Dong Yu
In many automatic speech recognition (ASR) tasks, an ideal model has to be applicable over multiple domains. In this paper, we propose to teach an all-rounder with experts in diffe…
Knowledge-aware Pronoun Coreference Resolution
Hongming Zhang, Yan Song, Yangqiu Song +1
Resolving pronoun coreference requires knowledge support, especially for particular domains (e.g., medicine). In this paper, we explore how to leverage different types of knowledge…
Learning Word Embeddings with Domain Awareness
Guoyin Wang, Yan Song, Yue Zhang +1
Word embeddings are traditionally trained on a large corpus in an unsupervised setting, with no specific design for incorporating domain knowledge. This can lead to unsatisfactory…
End-to-End Multi-Channel Speech Separation
Rongzhi Gu, Jian Wu, Shi-Xiong Zhang +6
The end-to-end approach for single-channel speech separation has been studied recently and shown promising results. This paper extended the previous approach and proposed a new end…
Learning discriminative features in sequence training without requiring framewise labelled data
Jun Wang, Dan Su, Jie Chen +4
In this work, we try to answer two questions: Can deeply learned features with discriminative power benefit an ASR system's robustness to acoustic variability? And how to learn the…
Encrypted Speech Recognition using Deep Polynomial Networks
Shi-Xiong Zhang, Yifan Gong, Dong Yu
The cloud-based speech recognition/API provides developers or enterprises an easy way to create speech-enabled features in their applications. However, sending audios about persona…