Jitter and shimmer voice-quality measurements have been successfully used to detect voice pathologies and classify different speaking styles. In this paper, we investigate the usefulness of jitter and shimmer voice measurements in the framework of the speaker diarization task. The combination of jitter and shimmer voice-quality features with the long-term prosodic and shortterm spectral features is explored in a subset of the Augmented Multi-party Interaction (AMI) corpus, a multi-party and spontaneous speech set of recordings. The best results have been obtained by fusing the voice-quality features with the prosodic ones at the feature level, and then fusing them with the spectral features at the score level. Experimental results show more than 20% relative DER improvement compared to the spectral baseline system.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 645323”.