A deep learning approach to integrate convolutional neural networks in speaker recognition-Reference-Cited by-同舟云学术

A deep learning approach to integrate convolutional neural networks in speaker recognition

Published:2020-06-03 Issue:3 Volume:23 Page:615-623
ISSN:1381-2416
Container-title:International Journal of Speech Technology
language:en
Short-container-title:Int J Speech Technol

Author:

Hourri Soufiane^ORCID,Nikolov Nikola S.,Kharroubi Jamal

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Link

http://link.springer.com/content/pdf/10.1007/s10772-020-09718-7.pdf

Reference42 articles.

1. Beigi, H. (2011). Fundamentals of speaker recognition (1st ed.). New York: Springer. https://doi.org/10.1007/978-0-387-77592-0 .

2. Bennani, Y., & Gallinari, P. (1994). Connectionist approaches for automatic speaker recognition. In: Proceedings of the Automatic Speaker Recognition, Identification and Verification.

3. Chen, Yh., Lopez-Moreno, I., Sainath, TN., Visontai, M., Alvarez, R., & Parada, C. (2015). Locally-connected and convolutional neural networks for small footprint speaker recognition. In: Proceedings of the Sixteenth Annual Conference of the International Speech Communication Association.

4. Cybenko, G. (1989). Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals and Systems, 2(4), 303–314.

5. Deng, L. (2014). A tutorial survey of architectures, algorithms, and applications for deep learning. Proceedings of the APSIPA Transactions on Signal and Information Processing.

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