Mechanism-Aware Neural Machine for Dialogue Response Generation Article Swipe
Ganbin Zhou
,
Ping Luo
,
Rongyu Cao
,
Fen Lin
,
Bo Chen
,
Qing He
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v31i1.10976
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v31i1.10976
To the same utterance, people's responses in everyday dialogue may be diverse largely in terms of content semantics, speaking styles, communication intentions and so on. Previous generative conversational models ignore these 1-to-n relationships between a post to its diverse responses, and tend to return high-frequency but meaningless responses. In this study we propose a mechanism-aware neural machine for dialogue response generation. It assumes that there exists some latent responding mechanisms, each of which can generate different responses for a single input post. With this assumption we model different responding mechanisms as latent embeddings, and develop a encoder-diverter-decoder framework to train its modules in an end-to-end fashion. With the learned latent mechanisms, for the first time these decomposed modules can be used to encode the input into mechanism-aware context, and decode the responses with the controlled generation styles and topics. Finally, the experiments with human judgements, intuitive examples, detailed discussions demonstrate the quality and diversity of the generated responses with 9.80% increase of acceptable ratio over the best of six baseline methods.
Related Topics
Concepts
Computer science
Utterance
Generative grammar
Mechanism (biology)
Context (archaeology)
Semantics (computer science)
ENCODE
Artificial intelligence
Generative model
Quality (philosophy)
Natural language processing
Biology
Epistemology
Chemistry
Programming language
Philosophy
Paleontology
Gene
Biochemistry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v31i1.10976
- https://ojs.aaai.org/index.php/AAAI/article/download/10976/10835
- OA Status
- diamond
- Cited By
- 90
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2604444020
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2604444020Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1609/aaai.v31i1.10976Digital Object Identifier
- Title
-
Mechanism-Aware Neural Machine for Dialogue Response GenerationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-02-12Full publication date if available
- Authors
-
Ganbin Zhou, Ping Luo, Rongyu Cao, Fen Lin, Bo Chen, Qing HeList of authors in order
- Landing page
-
https://doi.org/10.1609/aaai.v31i1.10976Publisher landing page
- PDF URL
-
https://ojs.aaai.org/index.php/AAAI/article/download/10976/10835Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://ojs.aaai.org/index.php/AAAI/article/download/10976/10835Direct OA link when available
- Concepts
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Computer science, Utterance, Generative grammar, Mechanism (biology), Context (archaeology), Semantics (computer science), ENCODE, Artificial intelligence, Generative model, Quality (philosophy), Natural language processing, Biology, Epistemology, Chemistry, Programming language, Philosophy, Paleontology, Gene, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
90Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 1, 2022: 4, 2021: 12, 2020: 22, 2019: 30Per-year citation counts (last 5 years)
- References (count)
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25Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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