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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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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 missing audio signal samples using a psychoacoustic model
Švento, Michal ; Záviška, Pavel (referee) ; Mokrý, Ondřej (advisor)
This bachelor thesis deals with the reconstruction of short-time damaged audio signal. The signal is represented by sparse signal representation using discrete Gabor transform. Convex optimalization tools are used for the reconstruction. The optimalization problem is solved using the Douglas—Rachford and Chambolle—Pock algorithm. Psychoacoustic model is involved in algorithm to obtain better results in objective metrics. The comparison is realised by an objective method SDR, PEMO-Q and also subjectively.
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Restoration of missing audio signal samples using a psychoacoustic model
Švento, Michal ; Záviška, Pavel (referee) ; Mokrý, Ondřej (advisor)
This bachelor thesis deals with the reconstruction of short-time damaged audio signal. The signal is represented by sparse signal representation using discrete Gabor transform. Convex optimalization tools are used for the reconstruction. The optimalization problem is solved using the Douglas—Rachford and Chambolle—Pock algorithm. Psychoacoustic model is involved in algorithm to obtain better results in objective metrics. The comparison is realised by an objective method SDR, PEMO-Q and also subjectively.
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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.
|
|
|
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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