ConflictNET: end-to-end learning for speech-based conflict intensity estimation - Vandana Rajan
2020 Intelligent Sensing Summer School
ConflictNET: end-to-end learning for speech-based conflict intensity estimation
Vandana Rajan, QMUL
Computational paralinguistics aims to infer human emotions, personality traits and behavioural patterns from speech signals. In particular, verbal conflict is an important example of human-interaction behaviour, whose detection would enable monitoring and feedback in a variety of applications. In this work, we propose an end-to-end convolutional-recurrent neural network architecture that learns conflict-specific features directly from raw speech waveforms.
As part of the 2020 Intelligent Sensing Summer School: http://cis.eecs.qmul.ac.uk/school2020...