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| Audio Segmentation and Classification in a Broadcast News Task |
| Lü Ping ; Yan Yong-hong |
| Zhongke Xinli Speech Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100080, China |
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Abstract This paper describes the work on the development of an audio segmentation and classification system applied to a broadcast news task for Chinese language. Three-phase automatic audio segmentation algorithm is provided. Audio stream is cut to audio segments (or sentences) by simply segmentation, fine segmentation and smoothing. Two different fine segmentation algorithms are given. They are dynamic noise tracking segmentation algorithm and segmentation based on mono-phone decoder algorithm respectively. Classifier based on mixture Gaussian model is used to classify audio segment into four groups: noise, music, male and female. The experiments on “Xin Wen Lian Bo” broadcast news show the performance of automatic segmentation and classification is almost equivalent to that of manual segmentation and classification.
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Received: 06 April 2005
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2006, Vol. 28 
