Influence of adaptive thresholding on peaks detection in audio data

Abstract

Many audio analysis systems employ peak picking procedure to produce the final decision. A typical scheme uses a thresholding function to minimise detection errors where its form depends on the structure of the input signal. The paper covers the problem of an adaptive thresholding function estimation. Using the genetic algorithm to optimise the components of the thresholding function we have determined the level of importance of individual local statistics on the final function representation. The proposed method has been used to tune the peak detection procedure to identify the change points in an audio signal. In the result of the heuristic configuration, the best accuracy of segment boundaries have been obtained for thresholding function built on top of two local statistics of the detection function and constant value. Finally, as an example, a comparison with the state–of–the–art scheme for audio segmentation was performed.