Speech Recognition System and Formant Based Analysis of Spoken Arabic Vowels

Authors:
Yousef Ajami Alotaibi;Amir Hussain
Affiliations:
Computer Eng. Dept., College of Computer & Information Sciences, King Saud University,;Department of Computing Science, Stirling University,
Venue:
FGIT '09 Proceedings of the 1st International Conference on Future Generation Information Technology
Year:
2009

Citing 3
Cited 1

Hidden Markov models for speech recognition

Technometrics
Discrete Time Processing of Speech Signals

Discrete Time Processing of Speech Signals
Formant based analysis of spoken Arabic vowels

BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication

Arabic vowels recognition based on wavelet average framing linear prediction coding and neural network

Speech Communication

Quantified Score

Hi-index	0.00

Visualization

Abstract

Arabic is one of the world's oldest languages and is currently the second most spoken language in terms of number of speakers. However, it 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 are explored using consonant-vowels-consonant (CVC) utterances. For this purpose, an HMM based recognizer was 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 facilitate future Arabic speech processing tasks such as vowel and speech recognition and classification.