Intelligent algorithms for movie sound tracks restoration

Authors:
Andrzej Czyżewski;Marek Dziubiński;Łukasz Litwic;Przemysław Maziewski
Affiliations:
Multimedia Systems Department, Gdansk University of Technology, Gdańsk, Poland;Multimedia Systems Department, Gdansk University of Technology, Gdańsk, Poland;Multimedia Systems Department, Gdansk University of Technology, Gdańsk, Poland;Multimedia Systems Department, Gdansk University of Technology, Gdańsk, Poland
Venue:
Transactions on Rough Sets V
Year:
2006

Citing 8
Cited 1

Adaptive signal processing

Adaptive signal processing
The JPEG still picture compression standard

Communications of the ACM - Special issue on digital multimedia systems
Digital Audio Restoration: A Statistical Model Based Approach

Digital Audio Restoration: A Statistical Model Based Approach
An Introduction to the Kalman Filter

An Introduction to the Kalman Filter
Advanced Digital Signal Processing and Noise Reduction

Advanced Digital Signal Processing and Noise Reduction
Intelligent algorithms for optical track audio restoration

RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Improving the readability of time-frequency and time-scalerepresentations by the reassignment method

IEEE Transactions on Signal Processing
An adaptive noise canceller with low signal distortion for speechcodecs

IEEE Transactions on Signal Processing

Speech coding employing intelligent signal processing techniques

Transactions on rough sets VII

Quantified Score

Hi-index	0.00

Visualization

Abstract

Two algorithms for movie sound tracks restoration are discussed in the paper. The first algorithm is the unpredictability measure computation applied to the psychoacoustic model-based broadband noise attenuation. A learning decision algorithm, based on a neural network, is employed for determining useful audio signal components acting as maskers of the noisy spectral parts. An application of the rough set decision system to this task is also considered. An iterative method for calculating the sound masking pattern is presented. The second of presented algorithms is the routine for precise evaluation of parasite frequency modulations (wow) utilizing sinusoidal components extracted from the sound spectrum. The results obtained employing proposed intelligent signal processing algorithms, as well as the relationship between both routines, will be presented and discussed in the paper.