Title :
Perceptual segmentation and component selection for sinusoidal representations of audio
Author :
Painter, Ted ; Spanias, Andreas
Author_Institution :
Handheld Comput. Div., Intel Corp., Hudson, MA, USA
fDate :
3/1/2005 12:00:00 AM
Abstract :
This paper presents two fundamental enhancements in a hybrid audio signal model consisting of sinusoidal, transient, and noise (STN) components. The first enhancement involves a novel application of a perceptual metric for optimal time segmentation for the analysis of transients. In particular, Moore and Glasberg´s model of partial loudness is modified for use with general signals and then integrated into a novel time segmentation scheme. The second, and perhaps more significant STN enhancement is concerned with a new methodology for ranking and selection of the most perceptually relevant sinusoids. A systematic procedure is developed for the selection of a compact set of sinusoids and comparative results are given to demonstrate the merit of this method.
Keywords :
audio coding; channel bank filters; loudness; noise; transient analysis; Glasberg model; Moore model; hybrid audio signal model; optimal time segmentation; partial loudness; perceptual segmentation; sinusoidal representation; time segmentation scheme; Audio coding; Filter bank; Frequency estimation; Psychoacoustic models; Signal analysis; Signal processing; Signal synthesis; Speech coding; Steady-state; Transient analysis; Audio coding; psychoacoustics; segmentation; sinusoidal models;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
DOI :
10.1109/TSA.2004.841050