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Composite Subband Adaptive Speech Enhancement
Hovorka, Jaroslav ; Vlček, Čestmír (referee) ; Křesálek,, Vojtěch (referee) ; Sysel, Petr (advisor)
The thesis deals with single channel and multiple channel algorithms for speech enhancement. The goal of this work is to perform the deep analysis of both single channel and multiple channel algorithms in sense of their behaviour in noisy environment of combat vehicles and platforms. Based on this analysis a new composite speech enhancement algorithm will be designed. This new approach is expected to increase quality of the processed speech in military communications systems. These systems are characterised by their operation under very noisy conditions where background noise is very high and signal-to-noise ratio extremely low. These noisy conditions are typical for the range of military and combat platforms and vehicles.
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System for the support of comparison of algorithms for noise reduction in audiosignal
Bartoš, Jan ; Smékal, Zdeněk (referee) ; Míča, Ivan (advisor)
The main purpose is to create a system for working with audio-signal, which is user-friendly and ready for next expansion. The program is developed in the Qt library of the Linux Ubuntu 7.4 operating system with using of C/C++ language. Another purpose is to demonstrate the functionality of the program on simple channel speech. To this aim there are implemented algorithms of the spectral subtraction and of the spektrogram's tresholding with using of FFT algorithm. The parts of the work are the teoretical part of the GUI implementation and the implementation of denoising methods, a partial description of the program and his structure and instruction manual.
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Methods of noise suppression for speech recognition systems
Moldříková, Zuzana ; Smital, Lukáš (referee) ; Odstrčilík, Jan (advisor)
This diploma thesis deals with methods of noise suppression for speech recognition systems. In theoretical part are discussed basic terms of this topic and also methods for noise suppression. These are spectral subtraction, Wiener filtering, RASTA, mapping of spectrogram or algorithms based on noise estimation. In second part types of noise are analyzed, there is proposal and implementation of spectral subtraction method of noise suppression for speech recognition system. Also extensive testing of spectral subtractive algorithms in comparison with Wiener filter is conducted. Assessment of this testing is done with defined metrics, successfulness of recognition, recognition system score and signal to noise ratio.
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