M
Michael T. Johnson
Researcher at University of Kentucky
Publications - 154
Citations - 2835
Michael T. Johnson is an academic researcher from University of Kentucky. The author has contributed to research in topics: Speech processing & Speech enhancement. The author has an hindex of 28, co-authored 151 publications receiving 2454 citations. Previous affiliations of Michael T. Johnson include Purdue University & University of Texas at San Antonio.
Papers
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Journal ArticleDOI
Acoustic sequences in non-human animals: a tutorial review and prospectus.
Arik Kershenbaum,Arik Kershenbaum,Daniel T. Blumstein,Marie A. Roch,Çağlar Akçay,Gregory A. Backus,Mark A. Bee,Kirsten M. Bohn,Yan Cao,Gerald G. Carter,Cristiane Cäsar,Michael H. Coen,Stacy L. DeRuiter,Laurance R. Doyle,Shimon Edelman,Ramon Ferrer-i-Cancho,Todd M. Freeberg,Ellen C. Garland,Morgan L. Gustison,Heidi E. Harley,Chloé Huetz,Melissa Hughes,Julia Hyland Bruno,Amiyaal Ilany,Dezhe Z. Jin,Michael T. Johnson,Chenghui Ju,Jeremy Karnowski,Bernard Lohr,Marta B. Manser,Brenda McCowan,Eduardo Mercado,Peter M. Narins,Alex K. Piel,Megan G. Rice,Roberta Salmi,Kazutoshi Sasahara,Laela S. Sayigh,Yu Shiu,Charles T. Taylor,Edgar E. Vallejo,Sara Waller,Veronica Zamora-Gutierrez,Veronica Zamora-Gutierrez +43 more
TL;DR: A uniform, systematic, and comprehensive approach to studying sequences is proposed, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies.
Journal ArticleDOI
Time series classification using Gaussian mixture models of reconstructed phase spaces
TL;DR: The proposed approach has strong theoretical foundations based on dynamical systems and topological theorems, resulting in a signal reconstruction, which is asymptotically guaranteed to be a complete representation of the underlying system, given properly chosen parameters.
Proceedings ArticleDOI
Stress and Emotion Classification using Jitter and Shimmer Features
Xi Li,Jidong Tao,Michael T. Johnson,Joseph Soltis,Anne Savage,Kirsten M. Leong,John D. Newman +6 more
TL;DR: The appended jitter and shimmer features result in an increase in classification accuracy for several illustrative datasets, including the SUSAS dataset for human speaking styles as well as vocalizations labeled by arousal level for African elephant and Rhesus monkey species.
Journal ArticleDOI
On the assessment of stability and patterning of speech movements.
TL;DR: A new approach to speech movement trajectory analysis is introduced, where trajectories from multiple movement sequences are time- and amplitude-normalized, and the STI (spatiotemporal index) is computed to capture the degree of convergence of a set of trajectories onto a single, underlying movement template.
Journal ArticleDOI
Speech signal enhancement through adaptive wavelet thresholding
TL;DR: Overall results indicate that SNR and SSNR improvements for the proposed approach are comparable to those of the Ephraim Malah filter, with BWT enhancement giving the best results of all methods for the noisiest (-10db and -5db input SNR) conditions.