A Fast Audio Clustering Using Vector Quantization and Second Order Statistics

Details A Fast Audio Clustering Using Vector Quantization and Second Order Statistics A Fast Audio Clustering Using Vector Quantization and Second Order Statistics

2010-09-23

arxiv.org/abs/1009.4719v1

Computer Science

Sound

Scientific paper

This paper describes an effective unsupervised speaker indexing approach. We suggest a two stage algorithm to speed-up the state-of-the-art algorithm based on the Bayesian Information Criterion (BIC). In the first stage of the merging process a computationally cheap method based on the vector quantization (VQ) is used. Then in the second stage a more computational expensive technique based on the BIC is applied. In the speaker indexing task a turning parameter or a threshold is used. We suggest an on-line procedure to define the value of a turning parameter without using development data. The results are evaluated using 10 hours of audio data.

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