Earticle

초록

영어

Arabic, the world’s second most spoken language in terms of number of speakers, has not received much attention from the traditional speech processing research community. This study is specifically concerned with the analysis of vowels in modern standard Arabic dialect. The first and second formant values in these vowels are investigated and the differences and similarities between the vowels explored using consonant-vowels-consonant (CVC) utterances. For this purpose, a Hidden Markov Model (HMM) based recognizer is built to classify the vowels and the performance of the recognizer analyzed to help understand the similarities and dissimilarities between the phonetic features of vowels. The vowels are also analyzed in both time and frequency domains, and the consistent findings of the analysis are expected to enable future Arabic speech processing tasks such as vowel and speech recognition and classification.

목차

Abstract
 1. Background
  1.1. Arabic language and research
  1.2. Hidden Markov models
  1.3. Formant readings
  1.4. Goals
 2. Experimental Framework
  2.1. Recognition system overview
  2.2. Database
 3. Results
  3.1. Speech recognition analysis
  3.2. Formant based analysis
  3.3. Discussion
 4. Conclusions
 5. Acknowledgments
 6. References

키워드

저자

• Yousef Ajami Alotaibi [ Computer Eng. Dept., College of Computer & Information Sciences, King Saud University ]
• Amir Hussain [ Department of Computing Science, Stirling University ]

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