Automatic Speech Attribute Transcription (ASAT), an ITR project sponsored under the NSF grant (IIS-04-27113), is a cross-institute effort involving Georgia Institute of Technology, The Ohio State University, University of California at Berkeley, and Rutgers University. This project approaches speech recognition from a more linguistic perspective: unlike traditional ASR systems, humans detect acoustic and auditory cues, weigh and combine them to form theories, and then process these cognitive hypotheses until linguistically and pragmatically consistent speech understanding is achieved. A major goal of the ASAT paradigm is to develop a detection-based approach to automatic speech recognition (ASR) based on attribute detection and knowledge integration. We report on progress of the ASAT project, present a sharable platform for community collaboration, and highlight areas of potential interdisciplinary ASR research.
Bibliographic reference. Lee, Chin-Hui / Clements, Mark A. / Dusan, Sorin / Fosler-Lussier, Eric / Johnson, Keith / Juang, Biing-Hwang / Rabiner, Lawrence R. (2007): "An overview on automatic speech attribute transcription (ASAT)", In INTERSPEECH-2007, 1825-1828.