Title :
Spoken Arabic Digits Recognition Based on (GMM) for E-Quran Voice Browsing: Application for Blind Category
Author :
Nacereddine Hammami;Mouldi Bedda;Nadir Farah;Raouf Ouanis Lakehal-Ayat
Author_Institution :
Lab. LabGed, Univ. Badji Mokhtar Annaba, Annaba, Algeria
Abstract :
People with low or no visual ability must also be able to manipulate, operate and browse the electronic reading devices of the Quran by a simple use of the voice (operation known as Voice-In/Voice-Out). The main operations of navigation and exploration of these devices, as the movement between verses or between pages can be fully realized through a voice recognition system of Arabic numbers. In this paper, we propose the use of voice recognition of Arabic digits as a way to use these devices, for this purpose, we present the method of speech recognition based on: (GMM) classifier, known for its effectiveness and scalability in speech modeling and the leading approach in speech recognition feature extraction Delta-Delta Mel-frequency cepstral coefficients (MFCC). The experimental results with the obtained parameters demonstrate the effectiveness of the digit recognition on a dataset in 99.31% of cases, which is highly satisfactory compared to previous works on spoken Arabic digits speech recognition.
Keywords :
"Speech recognition","Mel frequency cepstral coefficient","Speech","Hidden Markov models","Feature extraction","Conferences","Speech processing"
Conference_Titel :
Advances in Information Technology for the Holy Quran and Its Sciences (32519), 2013 Taibah University International Conference on
DOI :
10.1109/NOORIC.2013.35