A hybrid model for speech synthesis

Author

Spanias, Andreas S.

Author_Institution

Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA

fYear

1990

fDate

1-3 May 1990

Firstpage

1521

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

Keywords

fast Fourier transforms; spectral analysis; speech analysis and processing; speech synthesis; frequency domain; hybrid model; random noise sequence; robust speech synthesis; short-time Fourier transform; spectral envelope; spectral shaping; speech analysis; speech synthesis; time-varying autoregressive moving-average; vocoders; waveform coders; Frequency estimation; Humans; Noise shaping; Power harmonic filters; Random sequences; Speech analysis; Speech coding; Speech enhancement; Speech processing; Speech synthesis;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1990., IEEE International Symposium on

Conference_Location

New Orleans, LA

Type

conf

DOI

10.1109/ISCAS.1990.112422

Filename

112422