Paper Info
Title
Audio segmentation and classification using a temporally weighted fuzzy C-means algorithm
Abstract
In this paper, we present a noble method to segment and classify audio stream using a temporally weighted fuzzy c-means algorithm (TWFCM). The proposed algorithm is utilized to determine the boundaries between different kinds of sounds in an audio stream; and then classify the audio segments into five classes of sound such as music, speech, speech with music background, speech with noise background, and silence. This is an enhancement on conventional fuzzy c-means algorithm, applied in audio segmentation and classification domain, by addressing and reflecting the matter of temporal correlations between the audio signals in the current and previous time. A 3-elements feature vector is utilized in segmentation and a 5-elements feature vector is utilized in classification by using TWFCM. The audio-cuts can be detected accurately by this method, and mistakes caused by audio effects can be eliminated in segmentation. Improved classification performance is also achieved. The application of this method is demonstrated in segmenting and classifying real-world audio data such as television news, radio signals, etc. Experimental results indicate that the proposed method outperforms the conventional FCM.
Year
DOI
Venue
2011
10.1007/978-3-642-21090-7_53
ISNN (2)
Keywords
Field
DocType
improved classification performance,weighted fuzzy c-means algorithm,classification domain,real-world audio data,audio stream,audio segmentation,audio signal,noble method,audio segment,audio effect,feature vector
Audio signal,Speech coding,Scale-space segmentation,Market segmentation,Computer science,Artificial intelligence,Feature vector,Pattern recognition,Audio segmentation,Segmentation,Fuzzy logic,Algorithm,Speech recognition
Conference
Volume
ISSN
Citations 
6676
0302-9743
4
PageRank 
References 
Authors
0.40
8
4
Name
Order
Citations
PageRank
Ngoc Thi Thu Nguyen140.40
Mohammad A. Haque29910.07
Cheol-Hong Kim3133.67
Jong-Myon Kim49125.99