Gender Identification from Arabic Speech Using Machine Learning-Reference-Cited by-同舟云学术

Gender Identification from Arabic Speech Using Machine Learning

Published:2020-09-06 Issue: Volume: Page:149-162
ISSN:2367-3370
Container-title:Modelling and Implementation of Complex Systems
language:
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Author:

Hamdi Skander^ORCID,Moussaoui Abdelouahab^ORCID,Oussalah Mourad^ORCID,Saidi Mohamed

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-58861-8_11

Reference25 articles.

1. Klaylat, S., Osman, Z., Hamandi, L., et al.: Emotion recognition in Arabic speech. Analog Integr. Circ. Sig. Process 96, 337–351 (2018). https://doi.org/10.1007/s10470-018-1142-4

2. Klaylat, S., Osman, Z., Hamandi, L., et al.: Enhancement of an Arabic speech emotion recognition system. Int. J. Appl. Eng. Res. 13(5), 2380–2389 (2018). ISSN 0973–4562

3. Rami, S., Alkhawaldeh, D.G.R.: Gender recognition of human speech using one-dimensional conventional neural network. Sci. Program. (2019). https://doi.org/10.1155/2019/7213717 . ISSN: 1058–9244

4. Livieris, I., Pintelas, E., Pintelas, P.: Gender recognition by voice using an improved self-labeled algorithm. Mach. Learn. Knowl. Extr. 1, 492–503 (2019). https://doi.org/10.3390/make1010030

5. Kabil, S., Muckenhirn, H., Magimai-Doss, M.: On learning to identify genders from raw speech signal using CNNs, pp. 287–291 (2018). https://doi.org/10.21437/Interspeech.2018-1240

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