MPSA-DenseNet: A novel deep learning model for English accent classification

Author:

Song Tianyu,Nguyen Linh Thi Hoai,Ta Ton VietORCID

Funder

Kyushu University

Publisher

Elsevier BV

Reference36 articles.

1. Classification of spoken english accents using deep learning and speech analysis;Al-Jumaili,2022

2. Advances in phone-based modeling for automatic accent classification;Angkititrakul;IEEE Trans. Audio Speech Lang. Process.,2006

3. Ardila, R., Branson, M., Davis, K., Henretty, M., Kohler, M., Meyer, J., Morais, R., Saunders, L., Tyers, F.M., Weber, G., 2020. Common Voice: A Massively-Multilingual Speech Corpus. In: Proceedings of the 12th Conference on Language Resources and Evaluation. LREC 2020, pp. 4211–4215.

4. A comparative study on native and non-native english accent classifications;Bhowmik,2022

5. Bird, J.J., Wanner, E., Ekárt, A., Faria, D.R., 2019. Accent classification in human speech biometrics for native and non-native english speakers. In: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments. pp. 554–560.

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