Papers › A Multilingual Virtual Guide for Self-Attachment Technique
A Multilingual Virtual Guide for Self-Attachment Technique
Alicia Jiayun Law, Ruoyu Hu, Lisa Alazraki, Anandha Gopalan, Neophytos Polydorou, Abbas Edalat
In this work, we propose a computational framework that leverages existing out-of-language data to create a conversational agent for the delivery of Self-Attachment Technique (SAT) in Mandarin. Our framework does not require large-scale human translations, yet it achieves a comparable performance whilst also maintaining safety and reliability. We propose two different methods of augmenting available response data through empathetic rewriting. We evaluate our chatbot against a previous, English-only SAT chatbot through non-clinical human trials (N=42), each lasting five days, and quantitatively show that we are able to attain a comparable level of performance to the English SAT chatbot. We provide qualitative analysis on the limitations of our study and suggestions with the aim of guiding future improvements.
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