Arabic Automatic Speech Recognition: A Systematic Literature Review

Abstract

Automatic Speech Recognition (ASR), also known as Speech-To-Text (STT) or computer speech recognition, has been an active field of research recently. This study aims to chart this field by performing a Systematic Literature Review (SLR) to give insight into the ASR studies proposed, especially for the Arabic language. The purpose is to highlight the trends of research about Arabic ASR and guide researchers with the most significant studies published over ten years from 2011 to 2021. This SLR attempts to tackle seven specific research questions related to the toolkits used for developing and evaluating Arabic ASR, the supported type of the Arabic language, the used feature extraction/classification techniques, the type of speech recognition, the performance of Arabic ASR, the existing gaps facing researchers, along with some future research. Across five databases, 38 studies met our defined inclusion criteria. Our results showed different open-source toolkits to support Arabic speech recognition. The most prominent ones were KALDI, HTK, then CMU Sphinx toolkits. A total of 89.47% of the retained studies cover modern standard Arabic, whereas 26.32% of them were dedicated to different dialects of Arabic. MFCC and HMM were presented as the most used feature extraction and classification techniques, respectively: 63% of the papers were based on MFCC and 21% were based on HMM. The review also shows that the performance of Arabic ASR systems depends mainly on different criteria related to the availability of resources, the techniques used for acoustic modeling, and the used datasets.

Advancements in Arabic Text-to-Speech Systems: A 22-Year Literature Review

“…Text-to-speech synthesis requires a recorded speech corpus with high-quality text [12]. Building high-quality TTS systems involves several complex challenges, one of which is the design of the speech corpora.…”

“…The Arabic language is a semitic language, which differs from Indo-European languages in terms of phonetics, morphology, syntax, and semantics [10]. More than 1.5 billion persons utilize Arabic language worldwide, and more than 420 million individuals use it as their first language [11] [12]. Arabic is one of the six official languages of the United Nations [13].…”

“…• Classical Arabic: The Quran (the holy book of Islam) is written in this form and is the standard form of Arabic [17]. It was the language of poetry, grammar, medicine, and other disciplines throughout the Islamic Empire's classical period.…”

“…This form of Arabic is commonly seen in print media and is used in formal communication. Arabic speakers use this form of Arabic to connect with speakers of other dialects [16], [17]. • Dialectal Arabic (DA), also known as colloquial Arabic, is a variety of regional and national varieties of locally spoken dialects in the Arab world [16].…”

Sign languages and Deaf Communities

“…As humanity stands at the precipice of the Fourth Industrial Revolution, technology not only serves as an underpinning force but also as the vanguard, driving changes at unprecedented speeds (Khan, 2020). The continuous ebb and flow of technological advancements have profoundly altered the fabric of societies, marking an indelible imprint on the ways individuals connect, interact, and communicate (Dhouib et al, 2022). Within this vibrant tapestry of innovation, areas such as artificial intelligence, machine learning, and voice recognition have emerged as stalwarts, steering transformative pathways that affect myriad aspects of our daily lives.…”