Perceptual segmentation and component selection for sinusoidal representations of audio

Ted Painter, Andreas Spanias

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)149-161
Number of pages13
JournalIEEE Transactions on Speech and Audio Processing
Issue number2
StatePublished - Mar 2005


  • Audio coding
  • Psychoacoustics
  • Segmentation
  • Sinusoidal models

ASJC Scopus subject areas

  • Software
  • Acoustics and Ultrasonics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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