Hierarchical reinforcement learning for situated natural language generation
- Submitting institution
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The University of Hull
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1396277
- Type
- D - Journal article
- DOI
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10.1017/S1351324913000375
- Title of journal
- Natural language engineering
- Article number
- -
- First page
- 391
- Volume
- 21
- Issue
- 3
- ISSN
- 1351-3249
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2014
- URL
-
http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=9719879&fulltextType=RA&fileId=S1351324913000375
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 10
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper, which explores the connection between density and turn-taking, has impacted greatly on academic knowledge in the field of Computer Speech and Language. It is now cited as a standard reference for our understanding of spoken dialogue systems, for example: DOIs 10.18653/v1/W16-3631, 10.18653/v1/W17-5527. It has helped to consolidate Dethlefs’ reputation as a leading academic in the dialogue community leading her to review for all major ACL conferences, SIGDIAL and INTERSPEECH on an annual basis, as well as being area chair for “Discourse and Dialogue” at leading venues COLING-2016, ACL-2020 and mentoring chair at SIGDIAL 2020-2021.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -