自我依恋技术的多语言虚拟指南

Alicia Jiayun Law, Ruoyu Hu, Lisa Alazraki, A. Gopalan, Neophytos Polydorou, A. Edalat
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引用次数: 1

摘要

在这项工作中,我们提出了一个计算框架,利用现有的语言外数据来创建一个会话代理,用于用普通话传递自我依恋技术(SAT)。我们的框架不需要大规模的人工翻译,但它在保持安全性和可靠性的同时取得了相当的性能。我们提出了两种不同的方法,通过共情重写增加可用的响应数据。我们通过非临床人体试验(N = 42)将我们的聊天机器人与之前的英语SAT聊天机器人进行了比较,每次持续五天,并定量地表明我们能够达到与英语SAT聊天机器人相当的性能水平。我们对研究的局限性进行了定性分析,并提出了一些建议,以指导未来的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Multilingual Virtual Guide for Self-Attachment Technique
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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