Brooklyn College, Graduate Center
November 8, 12pm-1pm
Matching human performance is one of the most difficult problems for a variety of speech communication technologies, including automatic speech recognition, voice processing in hearing aids, and mobile telephony. One theory of human noise robustness is that listeners pick out reliable “glimpses” of a target sound and utilize contextual clues to fill in missing information using top-down knowledge. This talk presents work that brings both of these processes to machines.