A Database of Vocal Tract Resonance Trajectories for Research in Speech Processing - Robotics Institute Carnegie Mellon University

A Database of Vocal Tract Resonance Trajectories for Research in Speech Processing

Li Deng, Xiaodong Cui, Robert Pruvenok, Jonathan Huang, Safiyy Momen, Yanyi Chen, and Abeer Alwan
Conference Paper, Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '06), May, 2006

Abstract

While vocal tract resonances (VTRs, or formants that are defined as such resonances) are known to play a critical role in human speech perception and in computer speech processing, there has been a lack of standard databases needed for the quantitative evaluation of automatic VTR extraction techniques. We report in this paper on our recent effort to create a publicly available database of the first three VTR frequency trajectories. The database contains a representative subset of the TIMIT corpus with respect to speaker, gender, dialect and phonetic context, with a total of 538 sentences. A Matlab-based labeling tool is developed, with high-resolution wideband spectrograms displayed to assist in visual identification of VTR frequency values which are then recorded via mouse clicks and local spline interpolation. Special attention is paid to VTR values during consonantto- vowel (CV) and vowel-to-consonant (VC) transitions, and to speech segments with vocal tract anti-resonances. Using this database, we quantitatively assess two common automatic VTR tracking techniques in terms of their average tracking errors analyzed within each of the six major broad phonetic classes as well as during CV and VC transitions. The potential use of the VTR database for research in several areas of speech processing is discussed.

BibTeX

@conference{Deng-2006-9488,
author = {Li Deng and Xiaodong Cui and Robert Pruvenok and Jonathan Huang and Safiyy Momen and Yanyi Chen and Abeer Alwan},
title = {A Database of Vocal Tract Resonance Trajectories for Research in Speech Processing},
booktitle = {Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '06)},
year = {2006},
month = {May},
}