Speech recognition system and formant based analysis of spoken Arabic vowels

Alotaibi, Y.A.; Hussain, A.

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.

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: FGIT: International Conference on Future Generation Information Technology
• Start Date: Dec 10, 2009
• End Date: Dec 12, 2009
• Publication Date: 2009
• Deposit Date: Oct 17, 2019
• Publisher: Springer
• Pages: 50-60
• Series Title: Lecture Notes in Computer Science
• Series Number: 5899
• Series ISSN: 0302-9743
• Book Title: Future Generation Information Technology
• ISBN: 978-3-642-10508-1
• DOI: https://doi.org/10.1007/978-3-642-10509-8_7
• Keywords: MSA, Arabic, Vowels, Analysis, Speech, Recognition, Formants, HMM, ASR
• Public URL: http://researchrepository.napier.ac.uk/Output/1793530