REWIND Dataset: Privacy-preserving Speaking Status Segmentation from Multimodal Body Movement Signals in the Wild

arXiv:2403.01229v1 Announce Type: cross
Abstract: Recognizing speaking in humans is a central task towards understanding social interactions. Ideally, speaking would be detected from individual voice recordings, as done previously for meeting scenarios. However, individual voice recordings are hard to obtain in the wild, especially in crowded mingling scenarios due to cost, logistics, and privacy concerns. As an alternative, machine learning models trained on video and wearable sensor data make it possible to recognize speech by detecting its related gestures in …

abstract arxiv cs.ai cs.cv cs.lg dataset eess.sp humans interactions multimodal privacy segmentation social speaking type understanding voice