Sentence examples for extraction of acoustic from inspiring English sources

This article studies feature extraction of acoustic signals based on complex Morlet wavelet.

As research on the extraction of acoustic properties of speech for emotion recognition progresses, the need of investigating methods of feature extraction taking into account the necessities of real time processing systems becomes more important.

The first warp is called perceptual warp and applied during the extraction of acoustic features.

Automatic extraction of acoustic regions of interest from recordings captured in realistic clinical environments is a necessary preprocessing step in any cry analysis system.

The training phase starts with the extraction of acoustic features and the linguistic specification (i.e., contextual factors) for all training utterances.

The output of this segmentation system can then be utilized for performing further analysis involving extraction of required acoustic parameters from the identified acoustic parts.

We then digitised calls and carried out a semi-automatic extraction of six acoustic parameters of call elements, including mean and maximum acoustic frequency, the length of call elements and the location of the maximum frequency and amplitude within calls.

Accordingly, onomatopoeic sounds (including vocal sketching) may be advantageous as data in terms of the extraction of fine acoustic information.

The right anterior superior temporal gyrus has been assumed to have a prominent role in the extraction of slow acoustic elements [4], [19], [27], [29], [31].

Rather the auditory cortex seems to use the same network elements (GABAergic inhibition) to accomplish the demands of auditory processing which are more sophisticated than the extraction of simple acoustic features, e.g. object recognition and segregation.

In this paper we present a hierarchical framework for the extraction of spectro-temporal acoustic features.