
Ph.D., Elec. Eng. & Comp. Sc., MIT, 1996
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.
Teaching Statement:
Professor Hasegawa-Johnson teaches courses in Speech Acoustics, Digital Signal Processing, Audio Engineering, and Pattern Recognition.
Research Interests:
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.
For more information:
Prof. Hasegawa-Johnson's Home Page
Directory of Speech and Language Engineering Research at University of Illinois
Honors, Recognition, and Outstanding Achievements for Teaching
Honors, Recognition, and Outstanding Achievements for Research