In this paper we propose a preprocessing technique which allows to detect clicks, tones, overloads, clipping, etc., as well as to discover the parts of good-quality speech signal. As a result the performance of the speaker recognition system increases significantly. It should be noted that when describing noise detectors we aim only to provide a full list of algorithms we used as well as their parameters that we obtained in our experiments. The main goal of the paper is to demonstrate that using a set of simple detectors is very effective in detecting speech for speaker recognition task under the conditions of real noise.
CITATION STYLE
Simonchik, K., Aleinik, S., Ivanko, D., & Lavrentyeva, G. (2015). Automatic preprocessing technique for detection of corrupted speech signal fragments for the purpose of speaker recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9319, pp. 121–128). Springer Verlag. https://doi.org/10.1007/978-3-319-23132-7_15
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