Stochastic modeling of spectral adjustment for high quality pitch modification

Alexander Kain, Yannis Stylianou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations


We present a new algorithm for adjusting the magnitude spectrum when the fundamental frequency (F0) of a speech signal is altered. The algorithm exploits the correlation between F0 and the magnitude spectrum of speech as represented by line spectral frequencies (LSFs). This correlation is class-dependent, and thus a broad classification of the input is achieved by a Gaussian mixture model (GMM). The within-class dependencies of LSFs on F0 values are captured by constructing their joint probability densities using a series of GMMs, one for each speech class. The proposed system is used for post-processing the pitch modified signal. Perceptual tests showed that the addition of this post-processing system improves the naturalness of the pitch modified signal for large pitch modification factors.

Original languageEnglish (US)
Title of host publicationSignal Processing Theory and Methods IIAudio and ElectroacusticsSpeech Processing I
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)0780362934
StatePublished - 2000
Event25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey
Duration: Jun 5 2000Jun 9 2000

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149


Conference25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this