A Cluster-Based Speaker Diarization System Combined with Dimensionality Reduction Techniques
Keywords:
Speaker diarization, statistical model, segmentation clustering KL divergence.Abstract
In this article, we introduced an unsupervised speaker diarization system for speaker detection in noisy environments, we introduced a statistical mixture-based model to model the input segment and cluster features obtained using MFCC for effective speaker identification of this segment. The concepts of KL- divergence is considered to effectively identify a speaker based on the a maximum Likelihood estimate of the speaker.
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