Abstract
Accent detection which is also known as dialect recognition represents an emerging topic in speech processing. The classification of spoken accents can provide details about people background and their demographic information which can help in several domains. In this research, convolution neural network is utilised for the detection of three accent of English speakers including the American, British, and Indian accents. The data was collected from publicly available resources with speech samples from required English accents. Experimental results indicated the robustness of deep learning algorithms for the classification of English spoken accents which has the potential to be utilised in diverse applications specifically, within the security domain.
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Al-Jumaili, Z., Bassiouny, T., Alanezi, A., Khan, W., Al-Jumeily, D., Hussain, A.J. (2022). Classification of Spoken English Accents Using Deep Learning and Speech Analysis. In: Huang, DS., Jo, KH., Jing, J., Premaratne, P., Bevilacqua, V., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2022. Lecture Notes in Computer Science(), vol 13395. Springer, Cham. https://doi.org/10.1007/978-3-031-13832-4_24
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DOI: https://doi.org/10.1007/978-3-031-13832-4_24
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