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Spoken Language Understanding (SLU) aims to extract the semantics frame of user queries, which is a core component in a task-oriented dialog system.
The ATIS spoken language systems pilot corpus
Charles T. Hemphill, John J. Godfrey, and George R. Doddington · 1990
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
Earlier work this paper cites.
Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition
Erik F. Tjong Kim Sang and Fien De Meulder · 2003
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Generative and discriminative algorithms for spoken language understanding
Christian Raymond and Giuseppe Riccardi · 2007
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Spoken language understanding: Systems for extracting semantic information from speech
Gokhan Tur and Renato De Mori · 2011
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Investigation of recurrent-neural-network architectures and learning methods for spoken language understanding
Grégoire Mesnil, Xiaodong He, Li Deng, and Yoshua Bengio · 2013
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Convolutional neural network based triangular crf for joint intent detection and slot filling
Puyang Xu and Ruhi Sarikaya · 2013
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Recurrent neural networks for language understanding
Kaisheng Yao, Geoffrey Zweig, Mei-Yuh Hwang, Yangyang Shi, and Dong Yu · 2013
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Using recurrent neural networks for slot filling in spoken language understanding
Grégoire Mesnil, Yann Dauphin, Kaisheng Yao, Yoshua Bengio, Li Deng, Dilek Hakkani-Tur, Xiaodong He, Larry Heck, Gokhan Tur, Dong Yu, et al · 2014
Earlier work this paper cites.
Spoken language understanding using long short-term memory neural networks
Kaisheng Yao, Baolin Peng, Yu Zhang, Dong Yu, Geoffrey Zweig, and Yangyang Shi · 2014
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Recurrent conditional random field for language understanding
Kaisheng Yao, Baolin Peng, Geoffrey Zweig, Dong Yu, Xiaolong Li, and Feng Gao · 2014
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Recurrent neural network structured output prediction for spoken language understanding
Bing Liu and Ian Lane · 2015
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Recurrent neural network and lstm models for lexical utterance classification
Suman Ravuri and Andreas Stolcke · 2015
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End-to-end memory networks with knowledge carryover for multi-turn spoken language understanding
Yun-Nung Vivian Chen, Dilek Hakkani-Tür, Gokhan Tur, Jianfeng Gao, and Li Deng · 2016
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Multi-domain joint semantic frame parsing using bi-directional rnn-lstm
Dilek Hakkani-Tür, Gökhan Tür, Asli Celikyilmaz, Yun-Nung Chen, Jianfeng Gao, Li Deng, and Ye-Yi Wang · 2016
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Leveraging sentence-level information with encoder LSTM for semantic slot filling
Gakuto Kurata, Bing Xiang, Bowen Zhou, and Mo Yu · 2016
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Attention-based recurrent neural network models for joint intent detection and slot filling
Bing Liu and Ian Lane · 2016
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Joint online spoken language understanding and language modeling with recurrent neural networks
Bing Liu and Ian Lane · 2016
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Bi-directional recurrent neural network with ranking loss for spoken language understanding
N. T. Vu, P. Gupta, H. Adel, and H. Schütze · 2016
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A joint model of intent determination and slot filling for spoken language understanding
Xiaodong Zhang and Houfeng Wang · 2016
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Sequential dialogue context modeling for spoken language understanding
Ankur Bapna, Gokhan Tür, Dilek Hakkani-Tür, and Larry Heck · 2017
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Towards zero-shot frame semantic parsing for domain scaling
Ankur Bapna, Gokhan Tür, Dilek Hakkani-Tür, and Larry Heck · 2017
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A survey on dialogue systems: Recent advances and new frontiers
Hongshen Chen, Xiaorui Liu, Dawei Yin, and Jiliang Tang · 2017
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Onenet: Joint domain, intent, slot prediction for spoken language understanding
A stack-propagation framework with token-level intent detection for spoken language understanding
Libo Qin, Wanxiang Che, Yangming Li, Haoyang Wen, and Ting Liu · 2019
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Cross-lingual transfer learning for multilingual task oriented dialog
Sebastian Schuster, Sonal Gupta, Rushin Shah, and Mike Lewis · 2019
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Robust zero-shot cross-domain slot filling with example values
Darsh Shah, Raghav Gupta, Amir Fayazi, and Dilek Hakkani-Tur · 2019
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Joint slot filling and intent detection via capsule neural networks
Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, and Philip Yu · 2019
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Few-shot slot tagging with collapsed dependency transfer and label-enhanced task-adaptive projection network
Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, and Ting Liu · 2020
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Young-Bum Kim, Sungjin Lee, and Karl Stratos · 2017
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Domain attention with an ensemble of experts
Young-Bum Kim, Karl Stratos, and Dongchan Kim · 2017
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Multi-domain adversarial learning for slot filling in spoken language understanding
Bing Liu and Ian Lane · 2017
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Alice Coucke, Alaa Saade, Adrien Ball, Théodore Bluche, Alexandre Caulier, David Leroy, Clément Doumouro, Thibault Gisselbrecht, Francesco Caltagirone, Thibaut Lavril, et al · 2018
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Slot-gated modeling for joint slot filling and intent prediction
Chih-Wen Goo, Guang Gao, Yun-Kai Hsu, Chih-Li Huo, Tsung-Chieh Chen, Keng-Wei Hsu, and Yun-Nung Chen · 2018
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A self-attentive model with gate mechanism for spoken language understanding
Changliang Li, Liang Li, and Ji Qi · 2018
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How time matters: Learning time-decay attention for contextual spoken language understanding in dialogues
Shang-Yu Su, Pei-Chieh Yuan, and Yun-Nung Chen · 2018
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Attention-informed mixed-language training for zero-shot cross-lingual task-oriented dialogue systems
Zihan Liu, Genta Indra Winata, Zhaojiang Lin, Peng Xu, and Pascale Fung · 2020
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Coach: A coarse-to-fine approach for cross-domain slot filling
Zihan Liu, Genta Indra Winata, Peng Xu, and Pascale Fung · 2020
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Recent neural methods on slot filling and intent classification for task-oriented dialogue systems: A survey
Samuel Louvan and Bernardo Magnini · 2020
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Dialogue state induction using neural latent variable models
Qingkai Min, Libo Qin, Zhiyang Teng, Xiao Liu, and Yue Zhang · 2020
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Cosda-ml: Multi-lingual code-switching data augmentation for zero-shot cross-lingual nlp
Libo Qin, Minheng Ni, Yue Zhang, and Wanxiang Che · 2020
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Multi-domain spoken language understanding using domain-and task-aware parameterization
Libo Qin, Minheng Ni, Yue Zhang, Wanxiang Che, Yangming Li, and Ting Liu · 2020
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AGIF: An adaptive graph-interactive framework for joint multiple intent detection and slot filling
Libo Qin, Xiao Xu, Wanxiang Che, and Ting Liu · 2020
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From static to dynamic word representations: a survey
Yuxuan Wang, Yutai Hou, Wanxiang Che, and Ting Liu · 2020
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End-to-end slot alignment and recognition for cross-lingual NLU
Weijia Xu, Batool Haider, and Saab Mansour · 2020
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Graph lstm with context-gated mechanism for spoken language understanding
Linhao Zhang, Dehong Ma, Xiaodong Zhang, Xiaohui Yan, and Houfeng Wang · 2020
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Few-shot learning for multi-label intent detection
Yutai Hou, Yongkui Lai, Yushan Wu, Wanxiang Che, and Ting Liu · 2021
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Knowing where to leverage: Context-aware graph convolution network with an adaptive fusion layer for contextual spoken language understanding
L. Qin, W. Che, M. Ni, Y. Li, and T. Liu · 2021
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A co-interactive transformer for joint slot filling and intent detection
Libo Qin, Tailu Liu, Wanxiang Che, Bingbing Kang, Sendong Zhao, and Ting Liu · 2021
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Injecting word information with multi-level word adapter for chinese spoken language understanding
Dechuang Teng, Libo Qin, Wanxiang Che, Sendong Zhao, and Ting Liu · 2021
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