Speech Spectral Modeling and Speech Synthesis Using Finite Impulse Response Digital Filters

Date of Award

Fall 1982

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computational Modeling & Simulation Engineering

Program/Concentration

Modeling and Simulation

Committee Director

Stephen Zahorian

Committee Member

John W. Stoughton

Committee Member

Meghanad Wagh

Call Number for Print

Special Collections LD4331.E53G67

Abstract

Synthetic speech can be produced using a discrete-time model of human speech production. This model depends on the use of digital filters to model the spectral characteristics of the vocal tract. Speech spectra can be efficiently encoded using a set of principal components basis vectors; however, these vectors are not in a convenient mathematical form for directly determining a digital filter for the speech production model. If discrete cosine basis vectors are used to approximate the principal components basis vectors, then the cosine basis vector coefficients can be used to determine a Finite Impulse Response(FIR) digital filter for speech spectral modeling and speech synthesis. Three FIR filter formulations are presented and the corresponding analysis/synthesis systems are implemented on a digital computer. These formulations vary in terms of phase, spectral amplitude and frequency scaling, and computational complexity. The FIR analysis/synthesis systems are compared with the analysis/synthesis systems based on the principal components basis vectors and linear predictor filters(Infinite Impulse Response filters). A sentence preference test is used to compare the various systems. The results of the tests indicate that FIR digital filters can be used to produce high quality synthetic speech.

Rights

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DOI

10.25777/eqt4-z846

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