Mind-Machine Interaction Research Center
University of Florida
Department of Electrical and Computer Engineering
405 CSE, Bldg. 42
P.O. Box 116130
Gainesville, FL 32611-6130
Fax (904) 392-0044
E-mail: childers@drwho.ee.ufl.edu
Some illustrative examples of results include the ability to relate aspects of vocal fold mass and length, aperiodicity of vocal fold motion, and glottal area to vocal quality factors. A unique application of the results is a possible training aid for the hearing impaired. Another potential long range application would be to speech coding that would be based on segmenting speech according to phonetically related intervals that are synchronized with articulatory movement. This could provide a low bandwidth, high quality speech coding scheme.
Childers, D.G. and Ding, C., Articulatory Synthesis: Nasal Sounds and Male and Female Voices, Journal of Phonetics, vol. 19, 1991, pp. 453-464.
Wu, K. and Childers, D.G., Gender Recognition From Speech. Part I: Coarse Analysis, J. Acoust. Soc. Am., vol. 90, October, 1991, pp. 1828-1840.
Childers, D.G. and Wu, K., Gender Recognition From Speech. Part II: Fine Analysis, J. Acoust. Soc. Am., vol. 90, October, 1991, pp. 1841-1856.
Childers, D.G. and Lee, C-K., Vocal Quality Factors: Analysis, Synthesis, and Perception, J. Acoust. Soc. Am., vol. 90, November, 1991, pp. 2394-2410.
Lalwani, A.L. and Childers, D.G., Modeling Vocal Disorders Via Formant Synthesis, ICASSP, 1991, pp. 505-508.
Lalwani, A.L. and Childers, D.G., A Flexible Formant Synthesizer, ICASSP, 1991, pp. 777-780.
Prado, P.P.L., Shiva, E.H., and Childers, D.G., Optimization of Acoustic-to-Articulatory Mapping, ICASSP, 1992, pp II-33 to II-36.
Childers, D.G. and Bae, K.S., Detection of Laryngeal Function Using Speech and Electroglottographic Data, IEEE Transactions on Biomedical Engineering, vol. 39, no. 1, January, 1992, pp. 19-25
Childers, D. G., Signal Processing Methods for the Assessment of Vocal Disorders, Medical and Life Sciences Engineering, India (Special Issue on Biomedical Signal Processing), 1994.
Childers, D. G. and Wong, C. F., Measuring and Modeling Vocal Source-Tract Interaction, IEEE Trans. Biomed. Engr., vol. 41, June, 1994, pp. 663-671.
Childers, D. G. and Hu, H. T., Speech Synthesis by Glottal Linear Prediction, J. Acoust. Soc. Am., vol. 96. October, 1994, pp. 2026-2036.
Childers, D. G. and Ahn, C., Modeling the Glottal Volume-velocity Waveform for Three Voice Types, J. Acoust. Soc. Am., vol. 97, January, 1995, pp. 505-519.
Childers, D. G., Principe, J. C., and Ting, Y. T., Adaptive WRLS-VFF for Speech Analysis, IEEE Trans. Speech and Audio Processing, vol. 3, May, 1995, pp. 209-213.
Childers, D. G., Glottal Source Modeling for Voice Conversion, Speech Communication, vol. 16, 1995, pp. 127-138.
These are linear predictive coding, formant, and articulatory speech synthesis. The latter adjusts models of the position of the tongue, lips, jaw, velum, and other features to mimic the words produced by humans. We use these synthesizers to test hypotheses concerning human speech production. The experimental data for our studies is contained in a data base we have collected over the years from patients with vocal disorders, individuals with various voice types, and male and female voices. This data base is constantly undergoing extensive analysis to measure features considered important for voice modeling. To accomplish this task we have developed an interactive speech analysis software system to measure source-tract interaction, intervals of voiced and unvoiced sounds, automatic and user assisted inverse filtering, measurement of glottal volume velocity waveforms, as well as other speech related features.
I. H. Witten, Making Computers Talk, Prentice-Hall, 1986 (Paperback).
L. R. Rabiner and R. W. Schafer, Digital Processing of Speech Signals, Prentice-Hall, 1978.
J. R. Deller, J. G. Proakis, and J. H. L. Hansen, Discrete-Time Processing of Speech Signals, Macmillian, 1993.