JOURNAL ARTICLE

Source Separation and Echo Cancellation Using Independent Component Analysis and DWT

Shweta YadavMeena Chavan

Year: 2015 Journal:   International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering Vol: 4 (5)Pages: 4323-4327   Publisher: Ess And Ess Research Publications

Abstract

In recent telecommunication hands free communication is used widely. This hands free communication suffers from many technical problems like room reverberation, acoustic echo, source interference, background noise. This paper proposes with the objective of blind source separation from mixture of many audio source signals , along with echo cancelation. Recent statistical and computational method ICA examined for source separation & echo cancellation. ICA along with DWT worked efficiently in source separation and denoising. An objective component of data is extracted from a linear representation of data, where that data must be non Gaussian and independent or partially dependant. DWTs are applicable for non-parametric signals.

Keywords:
Independent component analysis Blind signal separation Echo (communications protocol) Source separation Reverberation Computer science Speech recognition Component (thermodynamics) Noise (video) Noise reduction Interference (communication) Gaussian Parametric statistics Stereophonic sound Separation (statistics) Artificial intelligence Acoustics Telecommunications Mathematics Machine learning Statistics Physics

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2
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0.26
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Topics

Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics

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