SADAS: A Dialogue Assistant System Towards Remediating Norm Violations in Bilingual Socio-Cultural Conversations
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866911770030899200 |
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| author | Hua, Yuncheng Li, Zhuang Luo, Linhao Satriadi, Kadek Ananta Feng, Tao Zhan, Haolan Qu, Lizhen Sharma, Suraj Zukerman, Ingrid Semnani-Azad, Zhaleh Haffari, Gholamreza |
| author_facet | Hua, Yuncheng Li, Zhuang Luo, Linhao Satriadi, Kadek Ananta Feng, Tao Zhan, Haolan Qu, Lizhen Sharma, Suraj Zukerman, Ingrid Semnani-Azad, Zhaleh Haffari, Gholamreza |
| contents | In today's globalized world, bridging the cultural divide is more critical than ever for forging meaningful connections. The Socially-Aware Dialogue Assistant System (SADAS) is our answer to this global challenge, and it's designed to ensure that conversations between individuals from diverse cultural backgrounds unfold with respect and understanding. Our system's novel architecture includes: (1) identifying the categories of norms present in the dialogue, (2) detecting potential norm violations, (3) evaluating the severity of these violations, (4) implementing targeted remedies to rectify the breaches, and (5) articulates the rationale behind these corrective actions. We employ a series of State-Of-The-Art (SOTA) techniques to build different modules, and conduct numerous experiments to select the most suitable backbone model for each of the modules. We also design a human preference experiment to validate the overall performance of the system. We will open-source our system (including source code, tools and applications), hoping to advance future research. A demo video of our system can be found at:~\url{https://youtu.be/JqetWkfsejk}. We have released our code and software at:~\url{https://github.com/AnonymousEACLDemo/SADAS}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_01736 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | SADAS: A Dialogue Assistant System Towards Remediating Norm Violations in Bilingual Socio-Cultural Conversations Hua, Yuncheng Li, Zhuang Luo, Linhao Satriadi, Kadek Ananta Feng, Tao Zhan, Haolan Qu, Lizhen Sharma, Suraj Zukerman, Ingrid Semnani-Azad, Zhaleh Haffari, Gholamreza Computation and Language Artificial Intelligence I.2.7 In today's globalized world, bridging the cultural divide is more critical than ever for forging meaningful connections. The Socially-Aware Dialogue Assistant System (SADAS) is our answer to this global challenge, and it's designed to ensure that conversations between individuals from diverse cultural backgrounds unfold with respect and understanding. Our system's novel architecture includes: (1) identifying the categories of norms present in the dialogue, (2) detecting potential norm violations, (3) evaluating the severity of these violations, (4) implementing targeted remedies to rectify the breaches, and (5) articulates the rationale behind these corrective actions. We employ a series of State-Of-The-Art (SOTA) techniques to build different modules, and conduct numerous experiments to select the most suitable backbone model for each of the modules. We also design a human preference experiment to validate the overall performance of the system. We will open-source our system (including source code, tools and applications), hoping to advance future research. A demo video of our system can be found at:~\url{https://youtu.be/JqetWkfsejk}. We have released our code and software at:~\url{https://github.com/AnonymousEACLDemo/SADAS}. |
| title | SADAS: A Dialogue Assistant System Towards Remediating Norm Violations in Bilingual Socio-Cultural Conversations |
| topic | Computation and Language Artificial Intelligence I.2.7 |
| url | https://arxiv.org/abs/2402.01736 |