Another Arabic Voice Command Dataset for Multiple Speech Processing Tasks

The expansion of Internet connectivity has revolutionized our daily lives, with people increasingly relying on smartphones and laptops for various tasks. This technological evolution has prompted the development of innovative solutions to enhance the quality of life for diverse populations, including the elderly and individuals with disabilities. Among the most impactful advancements are voice-command-enabled technologies such as SIRI and Google voice commands, which are built upon the foundation of Speech Recognition modules, a critical component in facilitating human-machine communication.Automatic Speech Recognition (ASR) has witnessed significant progress in achieving human-like performance through data-driven methods. In the context of our research, we have meticulously crafted an Arabic voice command dataset to facilitate advancements in ASR and other speech processing tasks. This dataset comprises 10 distinct commands spoken by 10 unique speakers, each repeated 10 times. Despite its modest size, the dataset has demonstrated remarkable performance across a range of speech processing tasks.The dataset was rigorously evaluated, yielding exceptional results. In ASR, it achieved an accuracy of 95.9%, showcasing its potential for effectively transcribing spoken Arabic commands. Furthermore, the dataset excelled in speaker identification, gender recognition, accent recognition, and spoken language understanding, with macro F1 scores of 99.67%, 100%, 100%, and 97.98%, respectively.This Arabic Voice Command Dataset represents a valuable resource for researchers and developers in the field of speech processing and human-machine interaction. Its quality and diversity make it a robust foundation for developing and testing ASR and other related systems, ultimately contributing to the advancement of voice-command technologies and their widespread accessibility.