Hynek Hermansky: Learning: It’s not just for machines anymore

Hynek Hermansky has been active in speech research for over 40 years, is a Life Fellow of IEEE, Fellow of the International Speech Communication Association, authored or co-authored more than 350 papers with over 20,000 citations, holds more than 20 patents and received IEEE James L. Flanagan Speech and Audio Processing Award, and ISCA Medal for Scientific Achievements. He started his career in 1972 at Brno University of Technology, obtained his D.Eng.. degree from the University of Tokyo, worked for Panasonic Technologies, U S WEST Advanced Technologies, the Oregon Graduate Institute, IDIAP Martigny, the Johns Hopkins University, and Google Deep Mind. Currently, he is a Researcher at Speech@FIT BUT, and an Emeritus Professor at the Johns Hopkins University.

Learning: It’s not just for machines anymore

Machine recognition of speech requires training on a large amount of speech training data. Subsequently, research in machine recognition of speech consists mainly of getting hands-on large amounts of speech training data combined, often by a try-and-error, with the appropriate combination of processing modules. Advances are mostly being evaluated by error rates observed in recognition of test data. Such a process may be missing one of the prime goals of scientific endeavor, which is to obtain new knowledge, applicable to other applications. We argue that speech data can be used to obtain relevant hearing knowledge, which is used in decoding messages in speech, and report on some experiments, which support this notion.

His talk takes place Wednesday, November 22, 2023 at 14:00 in E105.

Video recording of the talk is publicly available.