Analysis and compensation of stressed and noisy speech with application to robust automatic recognition
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
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The use of present day speech recognition techniques in many practical applications has demonstrated the need for improved algorithm formulation under varying acoustical environments. This paper describes a low-vocabulary speech recognition algorithm which provides robust performance in noisy environments with particular emphasis on characteristics due to stress. A stressed based source generator framework is formulated to achieve robust speech parameter characterization using a morphological constrained enhancement algorithm and stressed source compensation which is unique for each source generator across a stressed speaking class. An estimated source generator class sequence allows noise parameter enhancement and stress compensation schemes to adapt to changing speech generator types. A phonetic consistency rule is also employed based on inpiit, source genrrator partitioning. Average recognition rates for noisy stressful speech are shown to increase from an average 36.7% for a baseline recognizer, to 74.7% for the new recognition algorithm (a +38% improvenimt.). Tho new algorithm is also more consistent under varying noisy conditions as demonstrated by a decrease in standard deviation of recognition from 21.1 to 11.9, and a reduction in confusable word-pairs under noisy, stressed speaking conditions.