Help Me Heal: A Reinforced Polite and Empathetic Mental Health and Legal Counseling Dialogue System for Crime Victims
نویسندگان
چکیده
The potential for conversational agents offering mental health and legal counseling in an autonomous, interactive, vitally accessible environment is getting highlighted due to the increased access information through internet mobile devices. A agent should be able offer higher engagement mimicking real-time sessions. ability empathize or comprehend feel another person’s emotions experiences a crucial quality that promotes effective therapeutic bonding rapport-building. Further, use of polite encoded language reflects nobility creates familiar, warm, comfortable atmosphere resolve human issues. Therefore, focusing on these two aspects, we propose Polite Empathetic Mental Health Legal Counseling Dialogue System (Po-Em-MHLCDS) victims crimes. To build Po-Em-MHLCDS, first create Dataset (MHLCD) by recruiting six employees who are asked converse with each other, acting as victim interchangeably following fixed stated guidelines. Second, MHLCD dataset annotated three informative labels, viz. strategies, politeness, empathy. Lastly, train Po-Em-MHLCDS reinforcement learning framework designing efficient reward function reinforce correct strategy, politeness empathy while maintaining contextual-coherence non-repetitiveness generated responses. Our extensive automatic evaluation demonstrate strength proposed system. Codes Data can accessed at https://www.iitp.ac.in/ ai-nlp-ml/resources.html#MHLCD https://github.com/Mishrakshitij/Po-Em-MHLCDS
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2023
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v37i12.26685