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A Multi-task Learning Framework for Politeness and Emotion Detection in Dialogues for Mental Health Counselling and Legal Aid by Priyanshu Priya; Mauajama Firdaus; Asif Ekbal is a Computer Science article available to read on EtoBox.

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The World Health Organization (WHO) has highlighted the need to greatly accelerate the prevention of crime and harassment against women and children, thereby promoting their mental well-being and gender parity to accomplish the United Nations Sustainable Development Goals by 2030. WHO estimates that globally around 736 million women 1 1 https://www.who.int/news-room/fact-sheets/detail/violence-against-women. and 1 billion children 2 2 https://www.who.int/health-topics/violence-against-children. have been subjected to violence. There is a global scarcity of mental healthcare workers 3 3 https://www.who.int/publications/i/item/9789240036703. ; hence, a conversational artificial intelligent agent that can converse with people in a polite and empathetic way like a human companion can be of great importance. Such systems can serve as first aid for the victims and the entry point for referring them to other support services they may need. Towards this goal, we create a POliteness and EMotion annotated dialogue dataset, named POEM comprising of 5,000 dialogues in English for mental health counselling and legal aid for women and children crime victims. Furthermore, we propose a novel multi

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Author

Priyanshu Priya; Mauajama Firdaus; Asif Ekbal

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)