{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/building-and-benchmarking-an-arabic-speech","title":"Building and benchmarking an Arabic Speech Commands dataset for small-footprint keyword spotting","arxiv_id":null,"date":"2021-05-07","proceeding":"Engineering Applications of Artificial Intelligence 2021 5","authors":["Abdulkader Ghandoura","Farouk Hjabo","Oumayma Al Dakkak"],"abstract":"The introduction of the Google Speech Commands dataset accelerated research and resulted in a variety of new deep learning approaches that address keyword spotting tasks. The main contribution of this work is the building of an Arabic Speech Commands dataset, a counterpart to Google’s dataset. Our dataset consists of 12,000 instances collected from 30 contributors and grouped into 40 keywords. We also report different experiments to benchmark this dataset using classical machine learning and deep learning approaches, the best of which is a Convolutional Neural Network with Mel-Frequency Cepstral Coefficients that achieved an accuracy of ∼98%. Additionally, we point out some key ideas to be considered in such tasks.","url_abs":"https://doi.org/10.1016/j.engappai.2021.104267","url_pdf":"https://doi.org/10.1016/j.engappai.2021.104267","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"building-and-benchmarking-an-arabic-speech","repo_url":"https://github.com/fresher96/arabic-speech-commands","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"keyword-spotting","task_name":"Keyword Spotting"},{"task_slug":"small-footprint-keyword-spotting","task_name":"Small-Footprint Keyword Spotting"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}