Content-Based Classification, Search, and Retrieval of Audio
IEEE MultiMedia
Fast Recognition of Musical Genres Using RBF Networks
IEEE Transactions on Knowledge and Data Engineering
Audio signal segmentation and classification using fuzzy c-means clustering
Systems and Computers in Japan
Content-Based Audio Classification Using Support Vector Machines and Independent Component Analysis
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Real-time discrimination of broadcast speech/music
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
Classification of audio signals using Fuzzy c-Means with divergence-based Kernel
Pattern Recognition Letters
Automatic Music Genre Classification Using a Hierarchical Clustering and a Language Model Approach
MMEDIA '09 Proceedings of the 2009 First International Conference on Advances in Multimedia
IEEE Transactions on Multimedia
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
SVM-based audio classification for content-based multimedia retrieval
MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
Robust audio identification for MP3 popular music
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Pattern Recognition & Matlab Intro
Pattern Recognition & Matlab Intro
Automatic Music Genre Classification Using Bass Lines
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Selection of Training Instances for Music Genre Classification
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Content-based retrieval of audio data using a Centroid Neural Network
ISSPIT '10 Proceedings of the The 10th IEEE International Symposium on Signal Processing and Information Technology
Hierarchical audio content classification system using an optimal feature selection algorithm
Multimedia Tools and Applications
Audio segmentation and classification using a temporally weighted fuzzy C-means algorithm
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Classification of audio signals using gradient-based fuzzy c-means algorithm with divergence measure
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
Quick audio retrieval using multiple feature vectors
IEEE Transactions on Consumer Electronics
Editorial: advanced semantic and social multimedia technologies for future computing environment
Multimedia Tools and Applications
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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.