Multistage speaker diarization of broadcast news
IEEE Transactions on Audio, Speech, and Language Processing
Tuning-robust initialization methods for speaker diarization
IEEE Transactions on Audio, Speech, and Language Processing
Speaker diarization using low-cost wearable wireless sensors
Proceedings of the 3rd International Conference on Information and Communication Systems
A review on speaker diarization systems and approaches
Speech Communication
Audiovisual diarization of people in video content
Multimedia Tools and Applications
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The LIMSI RT-07S speaker diarization system for the conference and lecture meetings is presented in this paper. This system builds upon the RT-06S diarization system designed for lecture data. The baseline system combines agglomerative clustering based on Bayesian information criterion (BIC) with a second clustering using state-of-the-art speaker identification (SID) techniques. Since the baseline system provides a high speech activity detection (SAD) error around of 10% on lecture data, some different acoustic representations with various normalization techniques are investigated within the framework of log-likelihood ratio (LLR) based speech activity detector. UBMs trained on the different types of acoustic features are also examined in the SID clustering stage. All SAD acoustic models and UBMs are trained with the forced alignment segmentations of the conference data. The diarization system integrating the new SAD models and UBM gives comparable results on both the RT-07S conference and lecture evaluation data for the multiple distant microphone (MDM) condition.