Mark Allan Hasegawa-Johnson

Electrical and Computer Engineering
Mark Allan Hasegawa-Johnson
Mark Allan Hasegawa-Johnson
  • Electrical and Computer Engineering
2011 Beckman Institute MC 251
405 N. Mathews
Urbana Illinois 61801

Primary Research Area

  • Robotics, vision, and artificial intelligence - Speech recognition and processing

For more information

Statistical Speech Technology Group



Ph.D., Elec. Eng. & Comp. Sc., MIT, 1996


Mark Hasegawa-Johnson received his S.B., S.M., and Ph.D. degrees from MIT. Since 1999 he has been on the faculty at the University of Illinois, where he is now a Professor of Electrical and Computer Engineering. Dr. Hasegawa-Johnson is a Fellow of the Acoustical Society of America, and a Senior Member of the ACM and IEEE. His work on multimedia analytics was the topic of an article on; he is listed annually in Marquis Who's Who in the World. He is Associate Editor of the Journal of the Acoustical Society of America, and of the journal Laboratory Phonology, as well as being a member of the IEEE Speech and Language Technical Committee. He has given invited presentations at the 2008 National Academy of Engineering Japan-America Foundations of Engineering symposium (JAFOE), at the 2009 Machine Learning Summer School, at the 2011 International Conference on Machine Learning ISCA-ACL Symposium, and at conferences and corporations in fifteen countries. He is author or co-author of 50 journal articles, 190 conference papers and abstracts, and 4 patents. As of January, 2014, listed 2843 citations of his published work.

Teaching Statement

Professor Hasegawa-Johnson teaches courses in Speech Processing, Digital Signal Processing, Audio Engineering, Pattern Recognition, and Probability.

Research Statement

Dr. Hasegawa-Johnson's research is focused on the area of automatic speech recognition, with a particular focus on the mathematization of linguistic concepts. In the past five years, Dr. Hasegawa-Johnson's group has developed mathematical models of concepts from linguistics including a rudimentary model of pre-conscious speech perception (the landmark-based speech recognizer), a model that interprets pronunciation variability by figuring out how the talker planned his or her speech movements (tracking of tract variables from acoustics, and of gestures from tract variables), and a model that uses the stress and rhythm of natural language (prosody) to disambiguate confusable sentences. Recent application successes include:

* Speech recognition for talkers with cerebral palsy. The automatic system, suitably constrained, outperforms a human listener.

* Retrieval of broadcast television segments in four languages, based on queries specified in the international phonetic alphabet. The Illinois team, including students of Prof. Hasegawa-Johnson and Prof. Huang, took third place in this international competition, and was the only finalist from the United States.

* Automatic detection and labeling of non-speech audio events. The Illinois team, including students of Prof. Hasegawa-Johnson and Prof. Huang, took first place in this international competition.

* Teaching Chinese. Software and methods developed by Prof. Hasegawa-Johnson, together with his colleagues from Linguistics and Psychology, are being tested in Mandarin language classrooms at the University of Illinois.

Undergraduate Research Opportunities

Professor Hasegawa-Johnson typically supervises one or two undergraduate research projects per year, thesis research preferred. Past student theses include automatic recognition of musical genre, factorial HMMs for the automatic recognition of speech in music backgrounds, prosody-dependent speech recognition, image source modeling of room impulse response, sonorancy classification for automatic language ID, phonetic landmark detection for automatic language ID, and digital field recorder for acquisition of a natural audio database.

Research Interests

Acoustic phonetics, Audio signal processing and speech recognition, Speech and auditory physiology.

Research Areas

  • Acoustics
  • Adaptive signal processing
  • Biomedical imaging
  • Computer vision and pattern recognition
  • Image, video, and multimedia processing and compression
  • Machine learning
  • Machine learning and pattern recognition
  • Natural language processing
  • Random processes
  • Robotics and motion planning
  • Signal detection and estimation
  • Signal Processing
  • Speech processing
  • Speech recognition and processing

Teaching Honors

  • Daily Illini List of Teachers Ranked as Excellent by Their Students. Fall 2006 (ECE 544NA, Pattern Recognition), Spring 2004 (ECE 303, Audio Engineering), Spring 2003 (ECE 303, Audio Engineering), Spring 2002 (ECE 303, Audio Engineering), Spring 2001 (ECE 303, Audio Engineering)
  • Eminent Initiate, Alpha Chapter of Eta Kappa Nu (University of Illinois), May 3, 2003. Co-chapter-advisor, 2003-4. Chapter Advisor, 2004-6.

Research Honors

  • Principal Investigator, "Landmark Detection for LVCSR," Johns Hopkins CLSP Summer Workshop WS04, July and August, 2004. Funded by NSF, NSA, and DARPA; JHU PI is Fred Jelinek.
  • NSF CAREER Award, 1/1/2002-12/31/2007
  • Individual National Research Service Award, National Institutes of Health, 1998-1999.
  • Frederic Vinton Hunt Post-Doctoral Fellowship, Acoustical Society of America, 1996-1997.
  • Who's Who in America (national biography listing), 2006-10. Who's Who in Science and Engineering, 1992.
  • Paul L. Fortescue Graduate Fellow, IEEE, 1988-1989.

Courses Taught