Classification of background noises for hearing-aid applications.
A background-noise classification procedure is being developed for hearing-aid applications, wherein the hearing-aid response would be adjusted in response to changes in the noise environment. The classification procedure is based on measuring four signal features giving the fluctuations of the signal envelope and the mean frequency and low- and high-frequency slopes of the average spectrum. A more complicated procedure, based on determining the envelope modulation spectra in auditory critical bands, was also investigated and was found to offer no advantages over the simpler procedure. The accuracy of the classification procedure was determined for eleven everyday background noises under optimal conditions where the training and test noise sequences were different portions of the same short noise recording. A cluster analysis was used to determine the similarities among the feature vectors for the noises, and when the noises are grouped into a reduced number of clusters the noise-classification accuracy using the four features exceeds 90%.
Kates
J M
JM
Center for Research in Speech and Hearing Sciences, City University of New York, Graduate Center, New York 10036.
D016000:Cluster Analysis; D012048:Correction of Hearing Impairment; D006310:Hearing Aids / Q000706:statistics & numerical data*; D006801:Humans; D009622:Noise; D013067:Speech Perception