activity
20152022
most citedTask-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context

24 citations · 58 across the 15 of their papers we have counts for

collaborators

26 papers

cs.CL2022

A Generative User Simulator with GPT-based Architecture and Goal State Tracking for Reinforced Multi-Domain Dialog Systems

Hong Liu, Yucheng Cai, Zhijian Ou +2

Building user simulators (USs) for reinforcement learning (RL) of task-oriented dialog systems (DSs) has gained more and more attention, which, however, still faces several fundame…

cs.CL2022

Information Extraction and Human-Robot Dialogue towards Real-life Tasks: A Baseline Study with the MobileCS Dataset

Hong Liu, Hao Peng, Zhijian Ou +3

Recently, there have merged a class of task-oriented dialogue (TOD) datasets collected through Wizard-of-Oz simulated games. However, the Wizard-of-Oz data are in fact simulated da…

eess.AS20214 cited

Advancing CTC-CRF Based End-to-End Speech Recognition with Wordpieces and Conformers

Huahuan Zheng, Wenjie Peng, Zhijian Ou +1

Automatic speech recognition systems have been largely improved in the past few decades and current systems are mainly hybrid-based and end-to-end-based. The recently proposed CTC-…

eess.AS2021

Exploiting Single-Channel Speech For Multi-channel End-to-end Speech Recognition

Keyu An, Zhijian Ou

Recently, the end-to-end training approach for neural beamformer-supported multi-channel ASR has shown its effectiveness in multi-channel speech recognition. However, the integrati…

cs.CL2021

Multilingual and crosslingual speech recognition using phonological-vector based phone embeddings

Chengrui Zhu, Keyu An, Huahuan Zheng +1

The use of phonological features (PFs) potentially allows language-specific phones to remain linked in training, which is highly desirable for information sharing for multilingual…

eess.AS2021

Deformable TDNN with adaptive receptive fields for speech recognition

Keyu An, Yi Zhang, Zhijian Ou

Time Delay Neural Networks (TDNNs) are widely used in both DNN-HMM based hybrid speech recognition systems and recent end-to-end systems. Nevertheless, the receptive fields of TDNN…