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Comparative Analysis of Machine Learning Algorithms for Audio Signals Classification


Poonam Mahana, Gurbhej Singh


Vol. 15  No. 6  pp. 49-55


Research in the area of Audio Classification and retrieval, in comparison with closely related areas, such as speech recognition and speaker identification is relatively new Audio Classification is an important issue in current audio processing and content analysis researches.. Generally speaking, audio classification is a pattern recognition problem. Pattern recognition is the scientific discipline whose goal is the classification of objects into a number of categories or classes. Depending on the application, these objects can be images or signal waveform or any type of measurements that need to be classified. The goal of pattern recognition is to classify objects into a number of categories. The word pattern refers to the type of measurements that need to be categorized or classified. The measurement can be just about anything but typical examples are images and acoustic signals. The ongoing advancements in multimedia technologies drive the need for efficient classification of audio signals. This paper provides an improved audio classification and categorization technique using tw o M L algorithm.


Audio Signal Classification, SVM, Pre- processing, Pattern Recognition, Feature Extraction, Feature Selection, Sampling frequency, Frame forming and Pre-emphasized filter.