Modern standard Arabic based multilingual approach for dialectal Arabic speech recognition

Cross-Word Arabic Pronunciation Variation Modeling Using Part of Speech Tagging

“…The majority of Arabic corpora available for the task of acoustic modeling have non-diacritized transcription. (Elmahdy et al, 2009) also showed that grapheme-to-phoneme relation is only true for diacritized Arabic script. Hence fore, Arabic speech recognition has an obstacle because the lack of diacritized corpora.…”

“…Consequently, more hypotheses' words will be considered during decoding process which may reduce the accuracy. (Elmahdy et al, 2009) summarized some of the problems raised in Arabic speech recognition. They highlighted the following problems: Arabic phonetics, diacritization problem, grapheme-to-phoneme, and morphological complexity.…”

“…Also in noisy telephone channel, syllables outperformed the rate obtained using monophones, triphones, and words by 2.09%, 1.5%, and 0.9%, respectively. (Elmahdy et al, 2009) used acoustic models trained with large MSA news broadcast speech corpus to work as multilingual or multi-accent models to decode colloquial Arabic. (Khasawneh et al, 2004) compared the polynomial classifier that was applied to isolated-word speaker-independent Arabic speech and dynamic time warping (DTW) recognizer.…”

Developing an M-Learning Pilot for Qur'an and Its Sciences

“…[8] has recounted experiences to learn Arabic words and sporadic research adopted the method of Markov Chain. [9] has enumerated the various challenges faced by workers in the automatic identification on the Arabic language both spoken and text.…”

“…Panel displays and controls are written in any language around the Earth Qur'an as shown in figure [8][9][10][11]. The user can change places of the interface keys, forms and views.…”