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Deep learning based sound records analysis
Kramář, Denis ; Říha, Kamil (referee) ; Přinosil, Jiří (advisor)
This master thesis deals with the problem of audio-classification of the chainsaw logging sound in natural environment using mainly convolutional neural networks. First, a theory of grafical representation of audio signal is discussed. Following part is devoted to the machine learning area. In third chapter, some of present works dealing with this problematics are given. Within the practical part, used dataset and tested neural networks are presented. Final resultes are compared by achieved accuracy and by ROC curves. The robustness of the presented solutions was tested by proposed detection program and evaluated using objective criteria.
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Restoration of degraded audiosignals using sparse representations
Mokrý, Ondřej ; Veselý, Vítězslav (referee) ; Rajmic, Pavel (advisor)
This bachelor thesis is focused on the problem of inpainting a segment of missing samples in an audiosignal. The signal is represented as sparse vector using discrete Gabor transform. The problem of inpainting missing samples while preserving the sparsity of the representation is formulated as an optimisation task, which is then solved using Douglas-Rachford algorithm. In contrast with the state-of-the-art approaches, the algorithm is extended by proposing method for compensating the energy decrease which occurs in the restored signal.
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Presence and action of negative audio signals in environment
Renza, Pavel ; Šebesta, Vladimír (referee) ; Sigmund, Milan (advisor)
The thesis deals with negative influences of audio signals in the environment and the impact of the signals on human in psychological and physiological point of view. The origins of such audio signals as well as protection from their negative effects are considered. The thesis includes an overview study of standards and basic literature. Selected audio signals are presented using a program for negative audio signal analysis.
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Modern methods for restoration of degraded audiosignals
Mokrý, Ondřej ; Koldovský,, Zbyněk (referee) ; Rajmic, Pavel (advisor)
The master's thesis deals with the problem of restoring a block of missing samples in a digital audio signal. This problem is formulated as an optimization task, which seeks the sparsest time-frequency representation of a signal within the set of feasible reconstructed signals. Several particular formulations are discussed, namely the analyzing and the synthesizing model, both for convex and non-convex approaches. Suitable algorithms are proposed for solving these formulations, and in the convex case, the method is further enhanced by various procedures to compensate for the energy drop in the inpainted signal segment. The proposed algorithms are tested on real recordings, and their performance is shown to be competitive with the state-of-the-art.
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Restoration of signals after passing through the limiter with the use of psychoacoustic model
Kramář, Denis ; Rajmic, Pavel (referee) ; Záviška, Pavel (advisor)
This bachelor thesis deals with the use of sparse representaions for the purpose of restoration clipping-damaged audiosignal. First, a theory of limiter and signal limiting itself is discussed. Subsequently, some of present methods based on sparse representations theory are given. The theory of sparse representations is discussed in following chapture. After that is here described a psychoacoustic model and it's use for declipping. At the end of theoretical part, two methods dealing with this problem are introduced. First is based on synthesis model of signal using Douglas-Rachford algorithm. Second is based on analysis signal model using Chambolle-Pock algorithm. In the next part is their implementation in the Matlab environment. Finally, the result achieved by both algorithms are evaluated.
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Interactive web applications supporting education
Kratoš, Filip ; Koldovský, Zbyněk (referee) ; Rajmic, Pavel (advisor)
This term paper is focused on design of web applets using Javascript. It deals with design of six applets works with one-dimensional signals, especially audio-signals. The applets are Combination of Signals, Summation of Sine and Cosine Functions, Signal Filtering, Effect of Phase on Audio-signal, Effect of Aliasing, and Linear and Nonlinear Systems. Main themes of the paper are theoretical background for applets, implementation of one applet and design of the interfaces of other applets.
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Efficient implementation of methods for the restoration of damaged audio signals
Csiba, Hajnalka ; Rajmic, Pavel (referee) ; Mokrý, Ondřej (advisor)
This bachelor's thesis deals with the restoration of audio signals containing unknown samples at known locations using two algorithms. The first is the Janssen algorithm and the second is a method based on non-negative matrix factorization. Janssen algorithm is built on the principle of the autoregressive model. The restoration of the samples is performed in such a way that the restored signal matches the predicted model as precisely as possible. The algorithm based on non-negative matrix factorization is used to decompose the frequency spectrogram of the signal as the product of non-negative matrices.
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Deep learning based sound records analysis
Kramář, Denis ; Říha, Kamil (referee) ; Přinosil, Jiří (advisor)
This master thesis deals with the problem of audio-classification of the chainsaw logging sound in natural environment using mainly convolutional neural networks. First, a theory of grafical representation of audio signal is discussed. Following part is devoted to the machine learning area. In third chapter, some of present works dealing with this problematics are given. Within the practical part, used dataset and tested neural networks are presented. Final resultes are compared by achieved accuracy and by ROC curves. The robustness of the presented solutions was tested by proposed detection program and evaluated using objective criteria.
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Modern methods for restoration of degraded audiosignals
Mokrý, Ondřej ; Koldovský,, Zbyněk (referee) ; Rajmic, Pavel (advisor)
The master's thesis deals with the problem of restoring a block of missing samples in a digital audio signal. This problem is formulated as an optimization task, which seeks the sparsest time-frequency representation of a signal within the set of feasible reconstructed signals. Several particular formulations are discussed, namely the analyzing and the synthesizing model, both for convex and non-convex approaches. Suitable algorithms are proposed for solving these formulations, and in the convex case, the method is further enhanced by various procedures to compensate for the energy drop in the inpainted signal segment. The proposed algorithms are tested on real recordings, and their performance is shown to be competitive with the state-of-the-art.
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Restoration of signals after passing through the limiter with the use of psychoacoustic model
Kramář, Denis ; Rajmic, Pavel (referee) ; Záviška, Pavel (advisor)
This bachelor thesis deals with the use of sparse representaions for the purpose of restoration clipping-damaged audiosignal. First, a theory of limiter and signal limiting itself is discussed. Subsequently, some of present methods based on sparse representations theory are given. The theory of sparse representations is discussed in following chapture. After that is here described a psychoacoustic model and it's use for declipping. At the end of theoretical part, two methods dealing with this problem are introduced. First is based on synthesis model of signal using Douglas-Rachford algorithm. Second is based on analysis signal model using Chambolle-Pock algorithm. In the next part is their implementation in the Matlab environment. Finally, the result achieved by both algorithms are evaluated.
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