VTAR (Vocal Tract Acoustic Response) | Speech Communication Laboratory

A tool for vocal tract modeling and acoustic analysis

VTAR (Vocal Tract Acoustic Response) is a Matlab-based computer program for vocal tract acoustic response calculation. Based on a frequency-domain vocal tract model [Zhang and Espy-Wilson, 2004, J. Acoust.Soc. Am., 115(3), 1274], VTAR is able to model various complex sounds such as nasals, rhotics and liquids. With input in the form of vocal tract cross-sectional area functions, VTAR calculates the vocal tract acoustic response function and the formant frequencies and bandwidths. The user-friendly interface allows directed data input for defined categories: vowels, nasals, nasalized sounds, consonant, laterals, and rhotics. The program also provides an interface for input and modification of arbitrary vocal tract geometry configurations, which is ideal for research applications.

The latest version includes new features as follows:
(1) acoustic sensitivity function calculation for formants,
(2) area function modification for targeted formant pattern,
(3) susceptance plot calculation, which is useful particularly for nasalized vowel analysis,
(4) speech sound synthesis with source model options, and
(5) addition of a new set of area function data for liquid sounds extracted from MR (Magnetic Resonance) images.

The main features of VTAR have been introduced at the annual meetings of the Acoustical Society of America.

X.Zhou, Z. Zhang, C.Y. Espy-Wilson, (2004), “VTAR: A Matlab-based computer program for vocal tract acoustic modeling “, Journal of the Acoustical Society of America 2004, Vol. 115, No. 5, pp. 2543. (presentation)
C. Y.Espy-Wilson, X. Zhou, M. Tiede, S. Boyce, (2007), “New features in VTAR: A Matlab-based computer program for vocal tract acoustic modeling “, Journal of the Acoustical Society of America 2007, Vol. 121, No. 5, pp. 3136. (presentation)

We acknowledge the inspiration provided by Michel T.T.Jackson, Maeda (1981) and a previous partial MATLAB version provided to us by R. Scaife.

This work was supported by NIH Grant 1 R01 DC05250-01 awarded to Suzanne Boyce (University of Cincinnati), Carol Espy-Wilson (University of Maryland), and Mark Tiede (Haskins Lab and MIT Research Lab of Electronics)