Arabic Speech

Research on Arabic speech focuses on improving automatic speech recognition (ASR) and text-to-speech (TTS) systems, particularly for diverse dialects and impaired speech. Current efforts leverage large language models like BERT and end-to-end neural network architectures, along with techniques like data augmentation and adversarial training, to address challenges posed by dialectal variation, code-switching, and dysarthria. These advancements are crucial for bridging the language technology gap in Arabic, enabling broader access to information and communication technologies, and facilitating advancements in fields like healthcare and education.