Thesis Details

Codec Detection from Speech

Bachelor's Thesis Student: Jon Josef Academic Year: 2016/2017 Supervisor: Černocký Jan, prof. Dr. Ing.
Czech title
Codec Detection from Speech
Language
English
Abstract

This thesis deals with codec detection from compressed speech signal. The primary goal was to identify which features distinguish selected codecs, and then create an environment facilitating experiments with various types of classifiers and their configurations. Support vector machines and neural networks, modeled using the Keras library, were used. The main contribution of this work is the experimental part, in which the effects of the neural networks parameters are discussed. After tuning the parameters and finding their optimal values, the network achieved accuracy over 98% on a test set comprising data from six different codecs.

Keywords

Neural networks, codec classification, speech processing, LPC, Keras, machine learning,Support vector machines, SVM, GRU, LSTM, codec

Department
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
16 June 2017
Reviewer
Committee
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT), předseda
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Hliněná Dana, doc. RNDr., Ph.D. (DMAT FEEC BUT), člen
Rozman Jaroslav, Ing., Ph.D. (DITS FIT BUT), člen
Ryšavý Ondřej, doc. Ing., Ph.D. (DIFS FIT BUT), člen
Citation
JON, Josef. Codec Detection from Speech. Brno, 2017. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2017-06-16. Supervised by Černocký Jan. Available from: https://www.fit.vut.cz/study/thesis/18356/
BibTeX
@bachelorsthesis{FITBT18356,
    author = "Josef Jon",
    type = "Bachelor's thesis",
    title = "Codec Detection from Speech",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2017,
    location = "Brno, CZ",
    language = "english",
    url = "https://www.fit.vut.cz/study/thesis/18356/"
}
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