Deep learning approaches are still not very common in the speaker verification field. We investigate the possibility of using deep residual convolutional neural network with spectrograms as an input features in the text-dependent speaker verification task. Despite the fact that we were not able to surpass the baseline system in quality, we achieved a quite good results for such a new approach getting an 5.23% ERR on the RSR2015 evaluation part. Fusion of the baseline and proposed systems outperformed the best individual system by 18% relatively.
CITATION STYLE
Malykh, E., Novoselov, S., & Kudashev, O. (2017). On residual cnn in text-dependent speaker verification task. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10458 LNAI, pp. 593–601). Springer Verlag. https://doi.org/10.1007/978-3-319-66429-3_59
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