Novel Techniques for Dialectal Arabic Speech Recognition

Mohamed Elmahdy, Rainer Gruhn, Wolfgang Minker

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English

Springer-Verlag New York Inc.
12 February 2012

Computational linguistics; Speech recognition

Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers.

In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and Maximum A-Posteriori (MAP) to adapt existing phonemic MSA acoustic models with a small amount of dialectal ECA speech data. Speech recognition results indicate a significant increase in recognition accuracy compared to a baseline model trained with only ECA data.

By: Mohamed Elmahdy, Rainer Gruhn, Wolfgang Minker
Imprint: Springer-Verlag New York Inc.
Country of Publication: United States [Currently unable to ship to USA: see Shipping Info]
Edition: 2012
Dimensions: Height: 235mm, Width: 155mm, Spine: 9mm
Weight: 371g
ISBN: 9781461419051
ISBN 10: 1461419050
Pages: 110
Publication Date: 12 February 2012
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Fundamentals.- Speech Corpora.- Phonemic Acoustic Modeling.- Graphemic Acoustic Modeling.- Phonetic Transcription Using the Arabic Chat Alphabet.