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Using posterior probability based features to segment an audio signal as speech and music has been commonly used method. In this study Hidden-Markov-Model (HMM) based acoustic models are used to calculate posterior probabilities. Acoustic Models includes states of context-independent phones as modeling unit. Entropy and dynamism are found using via the posterior probabilities and these values are...
A new method to discriminate between speech and music related to the automatic transcription of broadcast news is presented. In the proposed method, a time series regularity, sample entropy (SampEn), is mainly used as an efficient feature to discriminate speech and music of broadcast audio stream. SampEn is a variant of the approximate entropy (ApEn) that measures the regularity of time series. Depending...
Human whistle could be a way to perform activation of different kind of devices, for example turn on and off a light in a smart room. Therefore, in this paper a human whistle detection and frequency estimation system is presented. Further, an investigation of human whistling and a robust non-linear feature extraction is presented. A system for robust performance due to sensor change and various noise...
Recently, a generalized correlation function called correntropy, extracting both the time structure and the statistical distribution of time series using kernel methods, have been proposed. In this work, the statistically independence criterion obtained using correntropy has been used in separation of different musical instrument samples playing the same note.
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