Blind Source Separation Approach for Audio Signals based on Support Vector Machine Classification
| Autor: | Otman Chakkor, CED Ibn Tofail, Houda Abouzid |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Audio signal
Computer science business.industry 020208 electrical & electronic engineering 020206 networking & telecommunications Pattern recognition 02 engineering and technology Blind signal separation Support vector machine Noise Audio visual 0202 electrical engineering electronic engineering information engineering Source separation Artificial intelligence business Humanoid robot Support vector machine classification |
| Zdroj: | Proceedings of the 2nd International Conference on Computing and Wireless Communication Systems. |
| DOI: | 10.1145/3167486.3167526 |
| Popis: | Audio signals are surrounding us everywhere, existing in many forms (speech, music, noise background, ...), but they exist all mixed together and separating them is a real serious problem. It is required to arrange them in order to be separated to use them an easy way in such many various applications such as blind source separation, extraction of speech segments, audio visual analysis,.... In this work, we introduce a new method to separate audio signals arrived mixed to a couple of microphones implemented on a head of a humanoid robot to solve the blind source separation (BSS) problem using the support vector machine (SVM). Thus, we provide a theoretical introduction to present the SVM method which has frequently been proposed for classification and regression tasks. The observations are classified by SVM method using some standard recordings which have been taken in a room.The experimental results after using the SVM technique are given at the end of this paper. |
| Databáze: | OpenAIRE |
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