Title :
Stochastic perceptual models of speech
Author :
Morgan, Nelson ; Bourland, H. ; Greenberg, Steven ; Hermansky, Hynek ; Wu, Su Lin
Author_Institution :
Int. Comput. Sci. Inst., Berkeley, CA, USA
Abstract :
We have developed a statistical model of speech (based on auditory perceptual criteria) that avoids a number of current constraining assumptions for statistical speech recognition systems, particularly the model of speech as a sequence of stationary segments consisting of uncorrelated acoustic vectors. We further wish to focus statistical modeling power on perceptually-dominant and information-rich portions of the speech signal, which may also be the parts of the speech signal with a better chance to withstand adverse acoustical conditions. We describe some of the theory, along with some preliminary experiments. These experiments suggest that the regions of acoustic signal containing significant spectral change are critical to the recognition of continuous speech
Keywords :
acoustic signal processing; hearing; speech processing; speech recognition; statistical analysis; stochastic processes; acoustical conditions; auditory perceptual criteria; continuous speech recognition; experiments; speech signal; stationary segments sequence; statistical speech model; statistical speech recognition systems; stochastic perceptual models; uncorrelated acoustic vectors; Computer science; Neural networks; Power system modeling; Signal processing; Speech enhancement; Speech processing; Speech recognition; Stochastic processes; Training data; Unsolicited electronic mail; Vents;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479605