Stress compensation and noise reduction algorithms for robust speech recognition

The problem of speech recognition in noisy, stressful environments is addressed. The main contribution is the achievement of robust recognition in diverse environmental conditions through the formulation of a series of speech-enhancement and stress-compensation preprocessing algorithms. These preprocessors produce speech or recognition features less sensitive to varying factors caused by stress and noise. Results from four recognition scenarios based on such preprocessing are reported. Neutral, stressful, noisy neutral, and noisy stressful speech styles are considered. Noise reduction is based on constrained iterative speech enhancement. Stress compensation algorithms are based on formant location, bandwidth, and intensity.<<ETX>>