Towards Neural Speaker Modeling in Multi-Party Conversation: The Task, Dataset, and Models
DOI:
https://doi.org/10.1609/aaai.v32i1.12140Keywords:
Dialog systems, Speaker modelingAbstract
In this paper, we address the problem of speaker classification in multi-party conversation, and collect massive data to facilitate research in this direction. We further investigate temporal-based and content-based models of speakers, and propose several hybrids of them. Experiments show that speaker classification is feasible, and that hybrid models outperform each single component.
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Published
2018-04-29
How to Cite
Meng, Z., Mou, L., & Jin, Z. (2018). Towards Neural Speaker Modeling in Multi-Party Conversation: The Task, Dataset, and Models. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.12140
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Student Abstract Track