<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The authors of this article deals with the implementation of a combination of techniques of the fuzzy system and artificial intelligence in the application area of non-linear noise and interference suppression. This structure used is called an Adaptive Neuro Fuzzy Inference System (ANFIS). This system finds practical use mainly in audio telephone (mobile) communication in a noisy environment (transport, production halls, sports matches, <italic>etc</italic>). Experimental methods based on the two-input adaptive noise cancellation concept was clearly outlined. Within the experiments carried out, the authors created, based on the ANFIS structure, a comprehensive system for adaptive suppression of unwanted background interference that occurs in audio communication and degrades the audio signal. The system designed has been tested on real voice signals. This article presents the investigation and comparison amongst three distinct approaches to noise cancellation in speech; they are LMS (least mean squares) and RLS (recursive least squares) adaptive filtering and ANFIS. A careful review of literatures indicated the importance of non-linear adaptive algorithms over linear ones in noise cancellation. It was concluded that the ANFIS approach had the overall best performance as it efficiently cancelled noise even in highly noise-degraded speech. Results were drawn from the successful experimentation, subjective-based tests were used to analyse their comparative performance while objective tests were used to validate them. Implementation of algorithms was experimentally carried out in Matlab to justify the claims and determine their relative performances.</p></abstract>

The authors of this article deals with the implementation of a combination of techniques of the fuzzy system and artificial intelligence in the application area of non-linear noise and interference suppression. This structure used is called an Adaptive Neuro Fuzzy Inference System (ANFIS). This system finds practical use mainly in audio telephone (mobile) communication in a noisy environment (transport, production halls, sports matches, etc). Experimental methods based on the two-input adaptive noise cancellation concept was clearly outlined. Within the experiments carried out, the authors created, based on the ANFIS structure, a comprehensive system for adaptive suppression of unwanted background interference that occurs in audio communication and degrades the audio signal. The system designed has been tested on real voice signals. This article presents the investigation and comparison amongst three distinct approaches to noise cancellation in speech; they are LMS (least mean squares) and RLS (recursive least squares) adaptive filtering and ANFIS. A careful review of literatures indicated the importance of non-linear adaptive algorithms over linear ones in noise cancellation. It was concluded that the ANFIS approach had the overall best performance as it efficiently cancelled noise even in highly noise-degraded speech. Results were drawn from the successful experimentation, subjective-based tests were used to analyse their comparative performance while objective tests were used to validate them. Implementation of algorithms was experimentally carried out in Matlab to justify the claims and determine their relative performances.

A Robust Approach For Acoustic Noise Suppression In Speech Using ANFIS

Department of Cybernetics and Biomedical Engineering, VSB – Technical University of Ostrava, 17. listopadu 15/2172, 708 33 Ostrava, Czech Republic

Journal of Electrical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"A Robust Approach For Acoustic Noise Suppression In Speech Using ANFIS"}

The authors of this article deals with the implementation of a combination of techniques of the fuzzy system and artificial intelligence in the application...

A Robust Approach For Acoustic Noise Suppression In Speech Using ANFIS

Publié en ligne: 05 déc. 2015

Pages: 301 - 310

Reçu: 01 déc. 2014

DOI: https://doi.org/10.2478/jee-2015-0050

Mots clés
adaptive neuro fuzzy inference system, background noise, colored noise, noise cancellation, voice communication

© 2015 Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A Robust Approach For Acoustic Noise Suppression In Speech Using ANFIS

Publié en ligne: 05 déc. 2015

Pages: 301 - 310

Reçu: 01 déc. 2014

DOI: https://doi.org/10.2478/jee-2015-0050

Mots clésadaptive neuro fuzzy inference system, background noise, colored noise, noise cancellation, voice communication

© 2015 Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
adaptive neuro fuzzy inference system, background noise, colored noise, noise cancellation, voice communication