Audio signal processing using time-frequency approaches: coding, classification, fingerprinting, and watermarking

Authors:
K. Umapathy;B. Ghoraani;S. Krishnan
Affiliations:
Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada;Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada;Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on time-frequency analysis and its applications to multimedia signals
Year:
2010

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Abstract

Audio signals are information rich nonstationary signals that play an important role in our day-to-day communication, perception of environment, and entertainment. Due to its non-stationary nature, time- or frequency-only approaches are inadequate in analyzing these signals. A joint time-frequency (TF) approach would be a better choice to efficiently process these signals. In this digital era, compression, intelligent indexing for content-based retrieval, classification, and protection of digital audio content are few of the areas that encapsulate a majority of the audio signal processing applications. In this paper, we present a comprehensive array of TF methodologies that successfully address applications in all of the above mentioned areas. A TF-based audio coding scheme with novel psychoacoustics model, music classification, audio classification of environmental sounds, audio fingerprinting, and audio watermarking will be presented to demonstrate the advantages of using time-frequency approaches in analyzing and extracting information from audio signals.