You are in:Home/Publications/Arabic Phonemes Recognition Engine: Building Recipe

Ass. Lect. Wael Ali Basiony Sultan :: Publications:

Title:
Arabic Phonemes Recognition Engine: Building Recipe
Authors: Wael A. Sultan; M. Hesham Farouk
Year: 2015
Keywords: Statistical modeling; Arabic Speech Recognition; HMM; Gaussian Mixtures; Phoneme Model; Insertion penalty
Journal: International Journal of Engineering Research and Technology (ijert)
Volume: 4
Issue: 10
Pages: 340-344
Publisher: ESRSA Publication
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

Arabic phonemes recognition is a very important step in most of Arabic speech recognition based applications. This work presents a recipe for building an efficient Arabic phonemes recognizer with HMMs trained by two databases for Modern Standard Arabic (MSA). HMM parameters such as number of states and number of GMMs per state are optimized. And a comparison between models trained with each database is given. HTK tool has been used in this work and 70.2% maximum recognition rate has been achieved which is very interesting compared with other researches.

Google ScholarAcdemia.eduResearch GateLinkedinFacebookTwitterGoogle PlusYoutubeWordpressInstagramMendeleyZoteroEvernoteORCIDScopus