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Understanding passenger intents and extracting relevant slots are important building blocks towards developing a contextual dialogue system responsible for handling certain vehicle-passenger interactions in autonomous vehicles (AV).
Multi-domain joint semantic frame parsing using bi-directional rnn-lstm
D. Hakkani-Tür, G. Tur, A. Celikyilmaz, Y.-N. V. Chen, J. Gao, L. Deng, and Y.-Y. Wang · 2016
Earlier work this paper cites.
Joint online spoken language understanding and language modeling with recurrent neural networks
B. Liu and I. Lane · 2016
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A joint model of intent determination and slot filling for spoken language understanding
X. Zhang and H. Wang · 2016
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A hierarchical lstm model for joint tasks
Q. Zhou, L. Wen, X. Wang, L. Ma, and Y. Wang · 2016
Cited alongside, same era.
Hierarchical rnn with static sentence-level attention for text-based speaker change detection
Z. Meng, L. Mou, and Z. Jin · 2017
Later among the works it cites.
Jointly modeling intent identification and slot filling with contextual and hierarchical information
L. Wen, X. Wang, Z. Dong, and H. Chen · 2018
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