Recent Advances in Spoken Language Understanding

Author(s):  
Renato De Mori
Author(s):  
Libo Qin ◽  
Tianbao Xie ◽  
Wanxiang Che ◽  
Ting Liu

Spoken Language Understanding (SLU) aims to extract the semantics frame of user queries, which is a core component in a task-oriented dialog system. With the burst of deep neural networks and the evolution of pre-trained language models, the research of SLU has obtained significant breakthroughs. However, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this article. In this paper, we survey recent advances and new frontiers in SLU. Specifically, we give a thorough review of this research field, covering different aspects including (1) new taxonomy: we provide a new perspective for SLU filed, including single model vs. joint model, implicit joint modeling vs. explicit joint modeling in joint model, non pre-trained paradigm vs. pretrained paradigm; (2) new frontiers: some emerging areas in complex SLU as well as the corresponding challenges; (3) abundant open-source resources: to help the community, we have collected, organized the related papers, baseline projects and leaderboard on a public website where SLU researchers could directly access to the recent progress. We hope that this survey can shed a light on future research in SLU field.


Author(s):  
Natalia Tomashenko ◽  
Antoine Caubrière ◽  
Yannick Estève ◽  
Antoine Laurent ◽  
Emmanuel Morin

1991 ◽  
Author(s):  
Lynette Hirschman ◽  
Stephanie Seneff ◽  
David Goodine ◽  
Michael Phillips

2020 ◽  
Author(s):  
Saad Ghojaria ◽  
Rahul Kotian ◽  
Yash Sawant ◽  
Suresh Mestry

Author(s):  
Yun-Nung Chen ◽  
Dilek Hakkani-Tür ◽  
Gokhan Tur ◽  
Jianfeng Gao ◽  
Li Deng

Author(s):  
Prashanth Gurunath Shivakumar ◽  
Naveen Kumar ◽  
Panayiotis Georgiou ◽  
Shrikanth Narayanan

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