Automatic Audio Segmentation Using the Generalized Likelihood Ratio

Wang, David, Vogt, Robert J., Mason, Michael W., & Sridharan, Sridha (2008) Automatic Audio Segmentation Using the Generalized Likelihood Ratio. In 2nd International Conference on Signal Processing and Communication Systems, 2008. ICSPCS 2008., IEEE, Gold Coast, Australia.

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This paper presents a novel technique for segmenting an audio stream into homogeneous regions according to speaker identities, background noise, music, environmental and channel conditions. Audio segmentation is useful in audio diarization systems, which aim to annotate an input audio stream with information that attributes temporal regions of the audio into their specific sources. The segmentation method introduced in this paper is performed using the Generalized Likelihood Ratio (GLR), computed between two adjacent sliding windows over preprocessed speech. This approach is inspired by the popular segmentation method proposed by the pioneering work of Chen and Gopalakrishnan, using the Bayesian Information Criterion (BIC) with an expanding search window. This paper will aim to identify and address the shortcomings associated with such an approach. The result obtained by the proposed segmentation strategy is evaluated on the 2002 Rich Transcription (RT-02) Evaluation dataset, and a miss rate of 19.47% and a false alarm rate of 16.94% is achieved at the optimal threshold.

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ID Code: 56166
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1109/ICSPCS.2008.4813705
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Institutes > Information Security Institute
Copyright Owner: Copyright 2008 IEEE
Deposited On: 09 Jan 2013 22:58
Last Modified: 24 Apr 2013 19:15

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