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논문검색

Neural Network Optimization by Genetic Algorithms for the Audio Classification to Speech and Music

원문정보

Saeed Balochian, Emad Abbasi Seidabad, Saman Zahiri Rad

보안공학연구지원센터(IJSIP) International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.6 No.3 2013.06 pp.47-54
피인용수 : 0건 (자료제공 : 네이버학술정보)

초록

영어

In this paper, the execution of some features based on wavelet transform are evaluated through classification of audio to speech and music using the MLP classifiers Optimized by Genetic Algorithm. Classification results show the wavelet features are completely successful in speech/music classification. Experimental comparisons using different wavelets are presented and discussed. By using some wavelet features, extracted from 1-second segments of the signal, we obtained 96.49% accuracy in the audio classification of the MLP classifiers optimized by genetic algorithm.

목차

Abstract
 1. Introduction
 2. Wavelet Transform and Feature Vectors
 3. Classification Algorithms
 4. Experiments
 5. Results and Discussion
 6. Conclusions
 References

키워드

저자정보

  • Saeed Balochian Department of Electrical engineering, Gonabad branch, Islamic Azad University
  • Emad Abbasi Seidabad Department of Electrical engineering, Gonabad branch, Islamic Azad University
  • Saman Zahiri Rad Department of Electrical engineering, Gonabad branch, Islamic Azad University

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자료제공 : 네이버학술정보

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