no code implementations • 10 May 2021 • Pengwei Wang, Xin Ye, Xiaohuan Zhou, Jinghui Xie, Hao Wang
In contrast to conventional pipeline Spoken Language Understanding (SLU) which consists of automatic speech recognition (ASR) and natural language understanding (NLU), end-to-end SLU infers the semantic meaning directly from speech and overcomes the error propagation caused by ASR.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +8
no code implementations • 24 Sep 2019 • Pengwei Wang, Liang-Chen Wei, Yong Cao, Jinghui Xie, Yuji Cao, Zaiqing Nie
End-to-end Spoken Language Understanding (SLU) is proposed to infer the semantic meaning directly from audio features without intermediate text representation.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • EMNLP 2018 • Yimeng Zhuang, Jinghui Xie, Yinhe Zheng, Xuan Zhu
Most models for learning word embeddings are trained based on the context information of words, more precisely first order co-occurrence relations.