Turkish Journal of Electrical Engineering and Computer Sciences




Most research in the field of digital speech technology has traditionally been conducted in only a few languages, such as English, French, Spanish, or Chinese. Numerous studies using distinctive phonetic features (DPFs) with different techniques and algorithms have been carried out during the last 3 decades, mainly in English, Japanese, and other languages of industrialized countries. DPF elements are based on a technique used by linguists and digital speech and language experts to distinguish between different phones by considering the lowest level of actual features during phonation. These studies have investigated the best performances, outcomes, and theories, especially those regarding digital speech recognition. The aim of this paper is to present the background of DPF theories and the usefulness thereof for digital speech and language processing. In addition, we highlight the background of Arabic language phonology compared to 2 well-known languages to enhance the current knowledge about this narrow language discipline. Finally, this work reviews the research dealing with DPF strategies for digital speech and language processing using computing and engineering techniques and theories. Based on the literature search conducted for this paper, we conclude that although the Arabic language is a very important and old Semitic language, hitherto it has suffered from a lack of modern research resources and theories on DPF elements.


Arabic, DPF, speech, MSA, ASR, neural network

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