BUT recognizer for noise and reverberated environments among the world's best
Speech recognition is "relatively easy" for close-talk microphones in clean environments. In noise and with distant mikes, the performances degrade rapidly. The funding agencies are aware of this and the U.S. IARPA organized ASpIRE (Automatic Speech recognition in Reverberant Environments) challenge, where recognizers for these difficult environments were compared. The BUT team - Martin Karafiát, Lukáš Burget, Igor Szöke, František Grézl - together with colleagues from Raytheon BBN and Johns Hopkins University, came up with a system that scored among the best in the “Single Microphone” category - http://www.dni.gov/index.php/newsroom/press-releases/210-press-releases-2015/1252-iarpa-announces-winners-of-its-aspire-challenge. Due to lion's share of the BUT team on the whole system, BUT folks are grabbing 2/3 of the 30.000US$ prize. To look under the hood of the system, see http://www.fit.vutbr.cz/~karafiat/pubs.php?id=10972. The crucial thing is to make the daty as messy as possible!