Earticle

초록

영어

This paper presents a new hierarchical phoneme recognition system using the SVM classifier and different feature representations based on mellin transform. The proposed architecture uses different representations with each group of phonemes of the speech database TIMIT which are distributed in a way to reduce the confusions between phonemes having similar articulatory strcuture. The main idea of this new architecture is based on the principle that each group of phonemes has his own characteristics which requires us to choose the adequate representation for the given group. Experiments have proven the robustness of our new hierarchical phoneme recognition system (called MMP) and the use of conventional feature representations based on mellin transform explains its superior recognition performance.

목차

Abstract
 1. Introduction
 2. Support Vector Machine
 3. Feature Extraction Techniques based Mellin Transform
  3.1 The Mellin Transform
  3.2 Mellin-MFCC based Features
  3.3 Mellin-PLP based Features
 4. Hierarchical Recognition Systems Architecture
 5. Experimental Conditions
 5. Results and Ddiscussion
 6. Conclusion
 References

키워드

저자

• Rimah Amami [ National School of Engineering, Tunis, Tunisia ]
• Noureddine Ellouze [ National School of Engineering, Tunis, Tunisia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605