We present Re:Member, a system that explores how emotionally expressive, memory-grounded interaction can support more engaging second language (L2) learning. By drawing on users' personal videos and generating stylized spoken questions in the target language, Re:Member is designed to encourage affective recall and conversational engagement. The system aligns emotional tone with visual context, using expressive speech styles such as whispers or late-night tones to evoke specific moods. It combines WhisperX-based transcript alignment, 3-frame visual sampling, and Style-BERT-VITS2 for emotional synthesis within a modular generation pipeline. Designed as a stylized interaction probe, Re:Member highlights the role of affect and personal media in learner-centered educational technologies.
@article{arxiv.2510.19030,
title = {Re:Member: Emotional Question Generation from Personal Memories},
author = {Zackary Rackauckas and Nobuaki Minematsu and Julia Hirschberg},
journal= {arXiv preprint arXiv:2510.19030},
year = {2025}
}