MFAB: A Multimodal Fine-Grained Attention Decoder With Boundary-Aware Multi-Task Learning for Backchannel Prediction
Backchannel prediction is a key component of human-like conversational AI, enabling systems to generate timely and contextually appropriate listener responses. Existing approaches primarily rely on encoder-based architectures that fuse audio and text features through simple concatenation, limiting their ability to capt...