Whether you are newly arrived in Egypt and need to know the words for 'bread' and 'apartment,' or a long-term resident who suddenly needs to know how to ask for a picture frame or complain of a sore throat, this dictionary is for you. Fully revised and expanded, the third edition of this unique and invaluable dictionary presents 6,500 words commonly needed by foreigners speaking Arabic in Egypt. Arabic words are written in a clear and consistent transcription system, plurals are given for all nouns, plurals and feminine forms are provided for all adjectives, and past tenses are given for all verbs. The dictionary also provides stress rules and basic charts of verb endings, negation of verbs, form and use of numbers, pronominal suffixes, and comparatives and superlatives.

Understanding Arabic is an exciting new collection of studies by authors who investigate and outline the practical corollaries of Badawi's theory of Arabic.

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.

This book constitutes revised selected papers from the 6th International Conference on Arabic Language Processing, ICALP 2017, held in Fez, Morocco, in October 2017. The 18 full papers presented in this volume were carefully reviewed and selected from 55 submissions. They were organized in topical sections named: machine translation systems; speech recognition and synthesis; text categorization, clustering and summarization; information retrieval systems; and Arabic NLP tools and applications.