Dr. Elliot Moore II received his bachelor's, master's, and Ph.D. degrees in electrical and computer engineering from the Georgia Institute of Technology in 1998, 1999, and 2003, respectively. His thesis work pertained to the study and application of speech analysis techniques in the classification and recognition of stress and emotion. In particular, his dissertation presented an in-depth analysis of objectively measurable features of speech that were useable in creating patterns of separation between normal voices and those exhibiting the emotional disorder of clinical depression.
After working in a post-doctorate position for about a year, Dr. Moore joined Georgia Tech as an assistant professor in the fall of 2004 and was appointed as the School's associate chair for Undergraduate Affairs in August 2017. He continues his research in using digital speech processing theory and analysis in the classification of human vocal patterns for determining speaker demographics (i.e., dialect, language, etc.), speaker characteristics (i.e., gender, dimensions, etc.), and speaker state (i.e., emotion, stress, etc.).
- Voice analysis
- Speech feature extraction
- Voice synthesis/ conversion
- Glottal waveform analysis, estimation, and quality evaluation
- Feature selection/ Pattern classification
- Outstanding Graduate Teaching Assistant Award (2003)
- National Science Foundation Fellow (1998-2001)
- President's Fellow (1998-2002)
- FACES Fellow (2002-2003)
- NSF CAREER Award (2006)
Barnwell III, T., Clements, M., Anderson, D.V., Moore, E., Lee, M., Ertan, E., Krishnan, V., Choi, W., Hu, J., Demiroglu, C., Whitehead, S. and Durey, A. S., "Low bit-rate coding of speech in harsh conditions using non-acoustic auxiliary devices", in Special Workshop in Maui: Lectures by the Masters in Signal Processing, Jan., 2004
Moore, E., Clements, M., Peifer, J., and Weisser, L, "Comparing Objective Feature Statistics of Speech for Classifying Clinical Depression," in Proceedings, 26th Annual Conference of IEEE Engineering in Medicine and Biology Society, 2004
Moore, E. and Clements, M., "Algorithm for automatic glottal waveform estimation without the reliance on precise glottal closure information," in Proceedings, ICASSP, Vol. 1, pgs. 101-104, 2004
Moore, E., Clements, M., Peifer, J., and Weisser, L "Investigating the Role of Glottal Features in Classifying Clinical Depression." Proceedings, 25th Annual Conference of IEEE Engineering in Medicine and Biology Society, Vol. 3, pp. 2849-2852, 2003.
Moore, E., Clements, M., Peifer, J., and Weisser, L "Analysis of Prosodic Variation in Speech for Clinical Depression." Proceedings, 25th Annual Conference of IEEE Engineering in Medicine and Biology Society, Vol. 3, pp. 2925-2928, 2003.
Moore, E. "Evaluating objective feature statistics of speech as indicators of vocal affect and depression" PhD Dissertation, Georgia Institute of Technology, Atlanta, GA 2003
Last revised August 31, 2020