A BiRGAT Model for Multi-intent Spoken Language Understanding with Hierarchical Semantic Frames Article Swipe
Hongshen Xu
,
Ruisheng Cao
,
Su Zhu
,
Sheng Jiang
,
Hanchong Zhang
,
Lu Chen
,
Kai Yu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2402.18258
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2402.18258
Previous work on spoken language understanding (SLU) mainly focuses on single-intent settings, where each input utterance merely contains one user intent. This configuration significantly limits the surface form of user utterances and the capacity of output semantics. In this work, we first propose a Multi-Intent dataset which is collected from a realistic in-Vehicle dialogue System, called MIVS. The target semantic frame is organized in a 3-layer hierarchical structure to tackle the alignment and assignment problems in multi-intent cases. Accordingly, we devise a BiRGAT model to encode the hierarchy of ontology items, the backbone of which is a dual relational graph attention network. Coupled with the 3-way pointer-generator decoder, our method outperforms traditional sequence labeling and classification-based schemes by a large margin.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2402.18258
- https://arxiv.org/pdf/2402.18258
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392340526
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- OpenAlex ID
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https://openalex.org/W4392340526Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2402.18258Digital Object Identifier
- Title
-
A BiRGAT Model for Multi-intent Spoken Language Understanding with Hierarchical Semantic FramesWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-02-28Full publication date if available
- Authors
-
Hongshen Xu, Ruisheng Cao, Su Zhu, Sheng Jiang, Hanchong Zhang, Lu Chen, Kai YuList of authors in order
- Landing page
-
https://arxiv.org/abs/2402.18258Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2402.18258Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2402.18258Direct OA link when available
- Concepts
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Computer science, Natural language processing, Spoken language, Artificial intelligence, Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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