Empathy and Persona of English vs. Arabic Chatbots: A Survey and Future Directions

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Abstract

There is a high demand for chatbots across a wide range of sectors. Human-like chatbots engage meaningfully in dialogues while interpreting and expressing emotions and being consistent through understanding the user’s personality. Though substantial progress has been achieved in developing empathetic chatbots for English, work on Arabic chatbots is still in its early stages due to various challenges associated with the language constructs and dialects. This survey reviews recent literature on approaches to empathetic response generation, persona modelling and datasets for developing chatbots in the English language. In addition, it presents the challenges of applying these approaches to Arabic and outlines some solutions. We focus on open-domain chatbots developed as end-to-end generative systems due to their capabilities to learn and infer language and emotions. Accordingly, we create four open problems pertaining to gaps in Arabic and English work; namely, (1) feature representation learning based on multiple dialects; (2) modelling the various facets of a persona and emotions; (3) datasets; and (4) evaluation metrics.

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APA

Hamad, O., Hamdi, A., & Shaban, K. (2022). Empathy and Persona of English vs. Arabic Chatbots: A Survey and Future Directions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13502 LNAI, pp. 525–537). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-16270-1_43

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