Dr. Tao Zhang, Ph.D. of Starkey Hearing Technologies

The cocktail party problem has remained to be one of the most difficult problems for hearing devices
even after decades of extensive research. One of the key challenges is to determine the desired talker in
a cocktail party. Recently, researchers have successfully demonstrated the decoding of auditory
attention using EEG, MEG or EMG (i.e. [1][2][3]). In addition, several research studies have attempted to
incorporate the decoded auditory attention information into speech enhancement solutions (i.e. [4][5]).
However, existing solutions are less optimal in the sense that auditory attention decoding is often
separate from speech enhancement. In this talk, we propose a joint auditory attention decoding and
multi-channel speech enhancement approach. The proposed approach eliminates the need of extracting
speech envelope of each talk, which is a very difficult problem in practice by itself. Furthermore, the
proposed solution is optimal in the sense that the attended talker’s speech is optimized using both
microphone inputs and EEG inputs in a united framework. Preliminary evaluation results are presented
to demonstrate the effectiveness of the algorithm. Finally, future research directions will be discussed.

Biography:

Tao Zhang received his B.S. degree in physics from Nanjing University, Nanjing, China in 1986, M.S.
degree in electrical engineering from Peking University, Beijing, China in 1989, and Ph.D. degree in
speech and hearing science from the Ohio-State University, Columbus, OH, USA in 1995. He joined the
Advanced Research Department at Starkey Laboratories, Inc. as a Sr. Research Scientist in 2001,
managed the DSP department from 2004 to 2008 and the Signal Processing Research Department from
2008 to 2019. Since 2019, he has been Director of the Algorithms (AI, ML and Signal Processing)
Department at Starkey Hearing Technologies, a global leader in providing innovative hearing
technologies. He has received many prestigious awards including Inventor of the Year Award, the Mount
Rainier Best Research Team Award, the Most Valuable Idea Award, the Outstanding Technical
Leadership Award and the Engineering Service Award at Starkey.
He is a senior member of IEEE and the Signal Processing Society and the Engineering in Medicine and
Biology Society. He serves on the IEEE AASP Technical Committee, the industrial relationship committee
and the IEEE ComSoc North America Region Board. He is an IEEE SPS Distinguished Industry Speaker and
the Chair of IEEE Twin-cities Signal Processing and Communication Chapter.
His current research interests include audio, acoustic, speech signal processing and machine learning;
multimodal signal processing and machine learning for hearing enhancement, health and wellness
monitoring; psychoacoustics, room and ear canal acoustics; ultra-low power real-time embedded
system design and device-phone-cloud ecosystem design. He has authored and coauthored 120+
presentations and publications, received 23 approved patents and had additional 30+ patents pending.

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