Note from the Editor

This special issue of the Journal consists of nearly two dozen articles that address both methodological approaches to Arabic Natural Language Processing and Automatic Speech Recognition as well as pilot-tested applications that are of commercial value. In keeping with prior special issues of this Journal, published under the auspices of the current Editor-in-Chief, this issue will consider both textbased (written) natural language communications as well as spoken language understanding as two sides of the same coin when studying Natural Language Processing. In addition, as reflected in the title, some of the key components of automatic speech recognition as they pertain to Arabic speech, such as speaker identification, speech synthesis, identifying regional accents, and evaluating natural language dialogue systems, are addressed using highly novel techniques and approaches. Given that the integrated study of both Natural Language Processing and Automatic Speech Recognition has proven to be the up and coming trend in the speech technology world today, as demonstrated at the recent Mobile Voice Conference, sponsored by AVIOS and William Meisel, President of TMA Associates, this issue well captures the zeitgeist by showing the leitmotif of the speech technology sciences as the integration of speech recognition with natural language understanding and generation. Volume 19, No. 2 brings together the work of approximately sixty (60) contributing authors from leading universities in the U.S., Europe, Asia, Africa, and the Middle East. The guest editors are eminent researchers in Arabic Automatic Speech Recognition and Arabic Natural Language Processing. But, even more important, their espousal of a weltanschauung of making software tools and resources free, open and available to developers and users is especially commendable, because it is this kind of commitment to both scholarship and open sourcing of language tools that will bring Arabic Natural Language Processing and Arabic Automatic Speech Recognition to the fore. The anthology contained in this volume traverses many areas. The authors have gone through a rigorous peer review process, with an acceptance rate of not more than 50 % of total submissions, wherein most articles published herein have been subjected to at least two phases of review and revision. Considered among the collection are some very intriguing and novel ways of addressing the language processing components from stemming to morphological analysis to Part of Speech (POS) tagging, to named entity recognition, to acoustic modeling, to continuous speech recognition, etc., as they pertain to the Arabic language and dialects, with particular attention paid to the specific requirements of Arabic language that rely heavily on diacritics to determine the meaning of a word. But most important, the papers contained in this special issue show how new tools in Arabic Natural Language Processing and in Arabic Automatic Speech Recognition efficaciously bridge the gap between Arabic and other languages so that Arabic can enjoy the full advantages of Natural Language Processing techniques and Automatic Speech Recognition tools (and machine learning algorithms) as other languages do. For example, the fine paper on machine learning algorithms for data mining tasks shows how these advances can aid non-English speakers in making use of tools and services that are required in order to work with the massive amount of knowledge available on the Internet. Or, the paper on acoustic echo cancellation using adaptive filtering algorithms for Quranic accents & Amy Neustein [email protected]