Re:Member: Emotional Question Generation from Personal Memories
This addresses the need for more engaging and personalized educational technologies for second language learners, though it appears incremental as it builds on existing methods for emotional synthesis and transcript alignment.
The authors tackled the problem of making second language learning more engaging by developing Re:Member, a system that generates emotionally expressive, memory-grounded questions from personal videos, resulting in a modular pipeline that aligns emotional tone with visual context to encourage affective recall.
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.