Name
Title | ||
|---|---|---|
An analysis of content-based classification of audio signals using a fuzzy c-means algorithm |
Abstract | ||
|---|---|---|
Content-based audio signal classification into broad categories such as speech, music, or speech with noise is the first step before any further processing such as speech recognition, content-based indexing, or surveillance systems. In this paper, we propose an efficient content-based audio classification approach to classify audio signals into broad genres using a fuzzy c-means (FCM) algorithm. We analyze different characteristic features of audio signals in time, frequency, and coefficient domains and select the optimal feature vector by employing a noble analytical scoring method to each feature. We utilize an FCM-based classification scheme and apply it on the extracted normalized optimal feature vector to achieve an efficient classification result. Experimental results demonstrate that the proposed approach outperforms the existing state-of-the-art audio classification systems by more than 11% in classification performance. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s11042-012-1019-y | Multimedia Tools Appl. |
Keywords | DocType | Volume |
Audio segmentation and classification,Fuzzy c-means algorithm,Multimedia,Database retrieval | Journal | 63 |
Issue | ISSN | Citations |
1 | 1380-7501 | 7 |
PageRank | References | Authors |
0.48 | 31 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad A. Haque | 1 | 99 | 10.07 |
| Jong-Myon Kim | 2 | 91 | 25.99 |