The DOI matches its Crossref record; 10 of the 11 references it cites were found in a registry or an index.
Convolutional neural networks for multi-topic dialog state tracking,
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In more recent end-to-end approaches for dialogue modeling, speech and feedback recognition can be seen as a classification task from user behavior to the state of the system or to the value of specific slots in a slot-filling dialogue state.
“In more recent end-to-end approaches for dialogue modeling, speech, and feedback recognition can be seen as a classification task from user behavior to the state of the system (Qian et al., 2017; Shi et al., 2017), or to the value of specific slots in a slot-filling dialogue state (Xu and Hu, 2018; Ma et al., 2020; Ouyang et al., 2020; Zhang et al., 2020).”
From Modeling Feedback in Interaction With Conversational Agents—A Review (2022) · cites this paper as Shi et al., 2017
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Neural Belief Tracker: Data-Driven Dialogue State Tracking
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“…modeling, speech, and feedback recognition can be seen as a classification task from user behavior to the state of the system (Qian et al., 2017; Shi et al., 2017), or to the value of specific slots in a slot-filling dialogue state (Xu and Hu, 2018; Ma et al., 2020; Ouyang et al., 2020; Zhang et…”
BackgroundA multichannel convolutional neural network for cross-language dialog state tracking
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Metadata
- Authors
- Shi, H., Ushio, T., Endo, M., Yamagami, K., & Horii, N.
- Affiliations
- Panasonic (Japan) (JP)
- Corresponding author
- Shi, Hongjie
- ORCID
- Ushio, Takashi
- Venue
- Lecture Notes in Electrical Engineering
- Publisher
- Springer Singapore
- Published
- 2016-12-25
- Pages
- 451-463
- ISSN
- 1876-1100 (ISSN-L)
- 1876-1119
- OpenAlex
- W2561293850
- Cited by
- 24
- References
- 11
- Citations by year
- 2023: 1 · 2022: 1 · 2021: 3 · 2020: 2 · 2019: 4 · 2018: 7 · 2017: 4 · 2016: 2
- FWCI
- 9.91
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in electrical engineering (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- dialogue state tracking, slot filling, convolutional neural networks
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