This work is an attempt to introduce a comprehensive benchmark for Arabic speech recognition, specifically tailored to address the challenges of telephone conversations in Arabic language. Arabic, characterized by its rich dialectal diversity and phonetic complexity, presents a number of unique challenges for automatic speech recognition (ASR) systems. These challenges are further amplified in the domain of telephone calls, where audio quality, background noise, and conversational speech styles negatively affect recognition accuracy. Our work aims to establish a robust benchmark that not only encompasses the broad spectrum of Arabic dialects but also emulates the real-world conditions of call-based communications. By incorporating diverse dialectical expressions and accounting for the variable quality of call recordings, this benchmark seeks to provide a rigorous testing ground for the development and evaluation of ASR systems capable of navigating the complexities of Arabic speech in telephonic contexts. This work also attempts to establish a baseline performance evaluation using state-of-the-art ASR technologies.

翻译：本研究旨在为阿拉伯语语音识别引入一个全面的评估基准，专门针对阿拉伯语电话通话场景中的挑战而设计。阿拉伯语以其丰富的方言多样性和语音复杂性为特点，为自动语音识别（ASR）系统带来了一系列独特的挑战。这些挑战在电话通话领域进一步加剧，因为音频质量、背景噪声和会话式语音风格都会对识别准确率产生负面影响。我们的工作致力于建立一个稳健的基准，该基准不仅涵盖广泛的阿拉伯语方言，还模拟了基于通话的真实通信条件。通过纳入多样化的方言表达并考虑通话录音的可变质量，该基准旨在为开发和评估能够在电话语境下处理阿拉伯语语音复杂性的ASR系统提供一个严格的测试平台。本研究还尝试利用最先进的ASR技术建立基线性能评估。