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：本文旨在引入一个针对阿拉伯语电话会话挑战的综合性语音识别基准。阿拉伯语以其丰富的方言多样性和语音复杂性为特征，给自动语音识别系统带来了诸多独特挑战。这些挑战在电话呼叫领域进一步加剧，因为音频质量、背景噪声和会话式语音风格会显著影响识别准确性。我们的研究工作旨在建立一个稳健的基准，不仅涵盖阿拉伯语方言的广泛谱系，还能模拟电话通信的真实场景。通过整合多样化的方言表达并考虑呼叫录音的可变质量，该基准旨在为开发和评估能够在电话语境中处理阿拉伯语音复杂性的ASR系统提供严格的测试平台。本研究还尝试利用最先进的ASR技术建立基线性能评估。