Noise suppression methods for robust speech processing

Robust speech processing in practical operating environments requires effective environmental and processor noise suppression. This report describes the technical findings and accomplishments during the reporting period for the research program funded to develop real-time, compressed speech analysis-synthesis algorithms whose performance is invariant under signal contamination. Fulfillment of this requirement is necessary to insure reliable secure compressed speech transmission within realistic military command and control environments. Overall contributions resulting from this research program include the understanding of how environmental noise degrades narrow band, coded speech, development of appropriate real-time noise suppression algorithms, and development of speech parameter identification methods that consider signal contamination as a fundamental element in the estimation process. This report describes the research and results in the areas of noise suppression using the dual input adaptive noise cancellation articulation rate change techniques, spectral subtraction and a description of an experiment which demonstrated that the spectral substraction noise suppression algorithm can improve the intelligibility of 2400 bps, LPC-10 coded, helicopter speech by 10.6 points. In addition summaries are included of prior studies in Constant-Q signal analysis and synthesis, perceptual modelling, speech activity detection, and pole-zero modelling of noisy signals. Three recent studies in speech modelling using the critical band analysis-synthesis transform and using splines are then presented. Finally a list of major publications generated under this contract is given.