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AI Twin: Enhancing ESL Speaking Practice through AI Self-Clones of a Better Me

Published: January 16, 2026 | arXiv ID: 2601.11103v1

By: Minju Park , Seunghyun Lee , Juhwan Ma and more

Potential Business Impact:

Helps people learn English by speaking like a better version of themselves.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

Advances in AI have enabled ESL learners to practice speaking through conversational systems. However, most tools rely on explicit correction, which can interrupt the conversation and undermine confidence. Grounded in second language acquisition and motivational psychology, we present AI Twin, a system that rephrases learner utterances into more fluent English and delivers them in the learner's voice. Embodying a more confident and proficient version of the learner, AI Twin reinforces motivation through alignment with their aspirational Ideal L2 Self. Also, its use of implicit feedback through rephrasing preserves conversational flow and fosters an emotionally supportive environment. In a within-subject study with 20 adult ESL learners, we compared AI Twin with explicit correction and a non-personalized rephrasing agent. Results show that AI Twin elicited higher emotional engagement, with participants describing the experience as more motivating. These findings highlight the potential of self-representative AI for personalized, psychologically grounded support in ESL learning.

Country of Origin
🇨🇦 Canada

Page Count
31 pages

Category
Computer Science:
Human-Computer Interaction