Articulatory synthesis with the aid of a neural net

Author

Rahim, M.G. ; Goodyear, C.C.

Author_Institution

Liverpool Univ., UK

fYear

1989

fDate

23-26 May 1989

Firstpage

227

Abstract

The authors describe the training and use of a multilayer perceptron (MLP) which performs a mapping from the spectra of vowels and nasal consonants, using examples spoken by a single speaker, to sets of area parameters for use in the vocal-tract-modelling filter of a speech synthesizer. Different MLP structures have been investigated using as input data either PARCOR coefficients or sample values of the spectrum. The trained MLP can be used to estimate the driving parameters for speech synthesis from natural utterances using this restricted phoneme set

Keywords

acoustic signal processing; neural nets; speech synthesis; MLP structures; PARCOR coefficients; area parameters; articulatory synthesis; driving parameters; examples; input data; mapping; multilayer perceptron; nasal consonants; natural utterances; neural net; restricted phoneme set; sample values; sets; single speaker; spectra of vowels; spectrum; speech synthesis; speech synthesizer; training; use; vocal-tract-modelling filter; Acoustic pulses; Control system synthesis; Filters; Lips; Multilayer perceptrons; Natural languages; Neural networks; Parameter estimation; Speech analysis; Speech synthesis;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on

Conference_Location

Glasgow

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1989.266406

Filename

266406