A hybrid model for speech synthesis

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

4 Scopus citations

Abstract

A hybrid model for speech analysis/synthesis is proposed. It relies on a time-varying autoregressive moving-average (ARMA) model and the short-time Fourier transform (STFT). The model is hybrid in that the periodic (narrowband) component in speech is represented in the frequency domain by a harmonic-based STFT, while the random component in speech is represented by a random noise sequence, appropriately shaped by the ARMA model. The time-varying ARMA model has a dual function (namely, it creates a spectral envelope that fits accurately the harmonic STFT components) and provides for the spectral shaping of random noise. This hybrid model essentially incorporates the benefits of waveform coders by employing the STFT and the benefits of traditional vocoders by using an appropriately shaped noise sequence; thus, it is expected to yield robust speech synthesis at low data rates.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Symposium on Circuits and Systems
PublisherPubl by IEEE
Pages1521-1524
Number of pages4
Volume2
StatePublished - 1990
Event1990 IEEE International Symposium on Circuits and Systems Part 3 (of 4) - New Orleans, LA, USA
Duration: May 1 1990May 3 1990

Other

Other1990 IEEE International Symposium on Circuits and Systems Part 3 (of 4)
CityNew Orleans, LA, USA
Period5/1/905/3/90

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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