Audio Brush: Editing Audio in the Spectrogram

  • A tool for editing audio signals in the spectrogram is presented. It allows manipulating the spectrogram of a signal at any chosen time-frequency resolution directly and to reconstruct the edited signal in HiFi quality - a capability that is usually not possible with the Fourier or wavelet transformation. Image processing and computer vision methods are applied to the spectrogram in order to identify, separate, eliminate and/or modify audio objects visually. As spectrograms give descriptive information about the sound, this tool allows editing audio in a "what you see is what you hear" style. This is enabled by a thorough investigation and exploitation of Gabor analysis and synthesis. We further propose to use a kind of zooming, as in visual painting tools, which results in a change of time and frequency resolution, and can be adapted for the task at hand. Results on applying this tool to erasing audio objects such as whistles, music, clapping and alike in audio tracks are presented.A tool for editing audio signals in the spectrogram is presented. It allows manipulating the spectrogram of a signal at any chosen time-frequency resolution directly and to reconstruct the edited signal in HiFi quality - a capability that is usually not possible with the Fourier or wavelet transformation. Image processing and computer vision methods are applied to the spectrogram in order to identify, separate, eliminate and/or modify audio objects visually. As spectrograms give descriptive information about the sound, this tool allows editing audio in a "what you see is what you hear" style. This is enabled by a thorough investigation and exploitation of Gabor analysis and synthesis. We further propose to use a kind of zooming, as in visual painting tools, which results in a change of time and frequency resolution, and can be adapted for the task at hand. Results on applying this tool to erasing audio objects such as whistles, music, clapping and alike in audio tracks are presented. Hence audio objects are automatically identied as visual objects in the spectrogram and eliminated therein. The cleaned signal is then reconstructed from the spectrogram in HiFi quality.show moreshow less

Download full text files

Export metadata

Statistics

Number of document requests

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:C. Gregor van den BoogaartGND, Rainer LienhartGND
URN:urn:nbn:de:bvb:384-opus4-1279
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/176
Series (Serial Number):Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (2005-10)
Type:Report
Language:English
Publishing Institution:Universität Augsburg
Release Date:2006/06/06
GND-Keyword:Digitale Audiotechnik; Audio-Mastering
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Multimedia und Maschinelles Sehen
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik