Automatic Conversation Turn-Taking Segmentation in Semantic Facet
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jung, D. | - |
dc.contributor.author | Cho, Yoon Sik | - |
dc.date.accessioned | 2024-01-09T06:06:36Z | - |
dc.date.available | 2024-01-09T06:06:36Z | - |
dc.date.issued | 2023 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/69978 | - |
dc.description.abstract | Turn-taking is a significant aspect of a smooth conversation system. Detecting end-of-turn can be difficult for automatic conversation systems, and this can cause misleading conversation systems. To make a conversational system recognizing turn transition points, we propose a token-level turn-taking segmentation using linguistic features. This task imitates the automatic speech recognition environment by organizing several settings. Moreover, we utilize GPT-2, which is well known as a pretrained generative language model, to be able to predict in token-level live text stream. We evaluate our model compared to RNN series models in general conversation datasets and explore model prediction with test sample scenarios. © 2023 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Automatic Conversation Turn-Taking Segmentation in Semantic Facet | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/ICEIC57457.2023.10049858 | - |
dc.identifier.bibliographicCitation | 2023 International Conference on Electronics, Information, and Communication, ICEIC 2023 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-85150452098 | - |
dc.citation.title | 2023 International Conference on Electronics, Information, and Communication, ICEIC 2023 | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordAuthor | Live Text Stream | - |
dc.subject.keywordAuthor | Token Classification | - |
dc.subject.keywordAuthor | Turn-taking Segmentation | - |
dc.description.journalRegisteredClass | scopus | - |
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