Modern standard Arabic based multilingual approach for dialectal Arabic speech recognition

In this paper we are proposing a new multilingual approach for dialectal Arabic speech recognition. Dialectal Arabic is only spoken and not used in written form in almost all domains and there is no standard for dialectal Arabic transcription. Therefore, preparing large training corpora for dialectal Arabic acoustic modeling is too difficult compared to Modern Standard Arabic. We have built several acoustic models with news broadcast speech corpus of Modern Standard Arabic speech. Egyptian Colloquial Arabic has been chosen in our work as a typical Arabic dialect example. We have collected Egyptian Colloquial Arabic connected digits corpus to evaluate our approach. We were able to use Modern Standard Arabic acoustic models as multilingual models to decode Egyptian Arabic. We were able to reach a recognition rate of 99.34% which is very satisfactory compared to the monolingual approach and compared to previous work in spoken Arabic digits speech recognition.

[1]  Jeff A. Bilmes,et al.  Novel approaches to Arabic speech recognition: report from the 2002 Johns-Hopkins Summer Workshop , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[2]  H. Soltau,et al.  Efficient handling of multilingual language models , 2003, 2003 IEEE Workshop on Automatic Speech Recognition and Understanding (IEEE Cat. No.03EX721).

[3]  Ramzi A. Haraty,et al.  CASRA+: A Colloquial Arabic Speech Recognition Application , 2007 .

[4]  Tanja Schultz,et al.  Language-independent and language-adaptive acoustic modeling for speech recognition , 2001, Speech Commun..

[5]  Mervat Fashal,et al.  Syllable-based automatic Arabic speech recognition , 2008 .

[6]  Slim Abdennadher,et al.  Survey on common Arabic language forms from a speech recognition point of view , 2009 .

[7]  Dimitra Vergyri,et al.  Cross-dialectal data sharing for acoustic modeling in Arabic speech recognition , 2005, Speech Commun..

[8]  Paul Lamere,et al.  Design of the CMU Sphinx-4 Decoder , 2022 .

[9]  Manfred K. Warmuth,et al.  THE CMU SPHINX-4 SPEECH RECOGNITION SYSTEM , 2001 .

[10]  Yousef Ajami Alotaibi.  Investigating spoken Arabic digits in speech recognition setting , 2005, Inf. Sci..

[11]  P. Fung,et al.  Multilingual spoken language processing , 2008, IEEE Signal Processing Magazine.

[12]  Dimitra Vergyri,et al.  Automatic Diacritization of Arabic for Acoustic Modeling in Speech Recognition , 2004 .