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Incorporating BERT With Probability-Aware Gate for Spoken Language Understanding

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成果类型:
期刊论文
作者:
Mei, Jie;Wang, Yufan;Tu, Xinhui;Dong, Ming;He, Tingting
作者机构:
[Dong, Ming; Tu, Xinhui; Wang, Yufan; Mei, Jie; He, Tingting] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smart, Wuhan 430079, Peoples R China.
[Dong, Ming; Tu, Xinhui; Wang, Yufan; Mei, Jie; He, Tingting] Cent China Normal Univ, Natl Language Resources Monitor & Res Ctr Network, Wuhan 430079, Peoples R China.
[Dong, Ming; Tu, Xinhui; Mei, Jie; He, Tingting] Cent China Normal Univ, Sch Comp Sci & Technol, Wuhan 430079, Peoples R China.
[Wang, Yufan] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
Training;Correlation;Bit error rate;Semantics;Natural languages;Logic gates;Filling;Natural language processing;spoken language understanding;intent detection;slot filling
期刊:
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
ISSN:
2329-9290
年:
2023
卷:
31
页码:
826-834
基金类别:
Key Research and Development Program of Hubei Province (Grant Number: 2020BAB017) Scientific Research Center Program of National Language Commission (Grant Number: ZDI135-135) 10.13039/501100012226-Fundamental Research Funds for the Central Universities (Grant Number: KJ02502022-0155 and CCNU22XJ037) 10.13039/501100004543-China Scholarship Council
机构署名:
本校为第一机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
Spoken language understanding (SLU) is an essential part of a task-oriented dialogue system, which mainly includes intent detection and slot filling. Some existing approaches obtain enhanced semantic representation by establishing the correlation between two tasks. However, those methods show little improvement when applied to BERT, since BERT has learned rich semantic features. In this paper, we propose a BERT-based model with the probability-aware gate mechanism, called PAGM (Probability Aware Gated Model). PAGM aims to learn the correlation between intent and slot from the perspective of pr...

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