Multimodal fusion of body movement signals for no-audio speech detection

No-audio Multimodal Speech Detection is one of the tasks in Media- Eval 2020, with the goal to automatically detect whether someone is speaking in social interaction on the basis of body movement signals. In this paper, a multimodal fusion method, combining signals obtained by an overhead camera and a wearable accelerometer, was proposed to determine whether someone was speaking. The proposed system directly takes the accelerometer signals as input, while using a pre-trained 3D convolutional network to extract the video features that work as input. Experiments on the No-audio Multimodal Speech Detection task show that our method outperforms all submissions of previous years.