Arabic phonemes transcription using data driven approach
Joint Authors
al-Khatib, Wasfi G.
al-Muhtasib, Husni Abd al-Ghani
Nahar, Khalid
al-Shafi, Mustafa
al-Ghamid, Mansuri
Source
The International Arab Journal of Information Technology
Issue
Vol. 12, Issue 3 (31 May. 2015)10 p.
Publisher
Publication Date
2015-05-31
Country of Publication
Jordan
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Arabic language and Literature
Topics
Abstract EN
The efficiency and correctness of continuous Arabic Speech Recognition Systems (ARS) hinge on the accuracy of the language phoneme set.
The main goal of this research is to recognize and transcribe Arabic phonemes using a data-driven approach.
We used the Hidden Markov Toolkit (HTK) to develop a phoneme recognizer, carrying out several experiments with different parameters, such as varying number of Hidden Markov Model (HMM) states and Gaussian mixtures to model the Arabic phonemes and find the best configuration.
We used a corpus consisting of about 4000 files, representing 5 recorded hours of modern standard Arabic of TV - News.
A statistical analysis for the phonemes length, frequency and mode was carried out, in order to determine the best number of states necessary to represent each phoneme.
Phoneme recognition accuracy of 56.79% was reached without using a language model.
The recognition accuracy increased to 96.3% upon using a bigram language model.
American Psychological Association (APA)
Nahar, Khalid& al-Muhtasib, Husni Abd al-Ghani& al-Khatib, Wasfi G.& al-Shafi, Mustafa& al-Ghamid, Mansuri. 2015. Arabic phonemes transcription using data driven approach. The International Arab Journal of Information Technology،Vol. 12, no. 3.
https://search.emarefa.net/detail/BIM-430919
Modern Language Association (MLA)
Nahar, Khalid…[et al.]. Arabic phonemes transcription using data driven approach. The International Arab Journal of Information Technology Vol. 12, no. 3 (May. 2015).
https://search.emarefa.net/detail/BIM-430919
American Medical Association (AMA)
Nahar, Khalid& al-Muhtasib, Husni Abd al-Ghani& al-Khatib, Wasfi G.& al-Shafi, Mustafa& al-Ghamid, Mansuri. Arabic phonemes transcription using data driven approach. The International Arab Journal of Information Technology. 2015. Vol. 12, no. 3.
https://search.emarefa.net/detail/BIM-430919
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-430919