Automated detection of alarm sounds.
Two approaches to the automated detection of alarm sounds are compared, one based on a change in overall sound level (RMS), the other a change in periodicity, as given by the power of the normalized autocorrelation function (PNA). Receiver operating characteristics in each case were obtained for different exemplars of four classes of alarm sounds (bells/chimes, buzzers/beepers, horns/whistles, and sirens) embedded in four noise backgrounds (cafeteria, park, traffic, and music). The results suggest that PNA combined with RMS may be used to improve current alarm-sound alerting technologies for the hard-of-hearing.
Auditory Behavioral Research Lab, Department of Communicative Disorders, University of Wisconsin, Madison, Wisconsin 53706, USA. ralutfi@wisc.edu
Robert A
RA
Lutfi
Inseok
I
Heo
D000162:Acoustics / Q000295:instrumentation*; D000465:Algorithms; D001307:Auditory Perception; D001331:Automation; D012048:Correction of Hearing Impairment / Q000523:psychology; D004867:Equipment Design; D006311:Hearing Disorders / Q000523:psychology; D006801:Humans; D009622:Noise; D010470:Perceptual Masking; D010507:Periodicity; D019986:Persons with Hearing Disabilities / Q000523:psychology / Q000534:rehabilitation; D012372:ROC Curve; D012815:Signal Processing, Computer-Assisted; D013016:Sound; D013997:Time Factors