is a  and a  at the University of Illinois Urbana-Champaign. He is the William L. Everitt Faculty Scholar in ECE and holds affiliations in the Department of Speech and Hearing Science, Coordinated Science Lab, , and Department of Computer Science. He also leads the , a new research initiative to make voice recognition technology more useful for people with a range of diverse speech patterns and disabilities. 
Hasegawa-Johnson has been on the faculty at the University of Illinois since 1999. His research addresses automatic speech recognition with a focus on the mathematization of linguistic concepts. His 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. Applications of his research include:

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

Provably correct unsupervised ASR, or ASR that can be trained using speech that has no associated text transcripts.


Equal Accuracy Ratio regularization: Methods that reduce the error rate gaps caused by gender, race, dialect, age, education, disability and/or socioeconomic class.


Automatic analysis of the social interactions between infant, father, mother, and older sibling during the first eighteen months of life.


Hasegawa-Johnson is currently Senior Area Editor of the journal IEEE Transactions on Audio, Speech and Language and a member of the ISCA Diversity Committee. He has published 308 peer-reviewed journal articles, patents, and conference papers in the general area of automatic speech analysis, including machine learning models of articulatory and acoustic phonetics, prosody, dysarthria, non-speech acoustic events, audio source separation, and under-resourced languages.
Education

Postdoctoral fellow, University of California at Los Angeles, 1996-1999

Ph.D., Massachusetts of Technology, 1996

M.S., Massachusetts Institute of Technology, 1989

Honors

2023: Fellow of the International Speech Communication Association for contributions to knowledge-constrained signal generation

2020: Fellow of the IEEE, for contributions to speech processing of under-resourced languages


2011: Fellow of the Acoustical Society of America, for contributions to vocal tract and speech modeling


2009: Senior Member of the Association for Computing Machinery


2004: Member, Articulograph International Steering Committee; CLSP Workshop leader, "Landmark-Based Speech Recognition”, Invited paper


2004: NAACL workshop on Linguistic and Higher-Level Knowledge Sources in Speech Recognition and Understanding


2003: List of faculty rated as excellent by their students


2002: NSF CAREER award


1998: NIH National Research Service Award


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