Lithologic classification using multilevel spectral characteristics

Neural network classification of gunshots using spectral characteristics

The paper describes neural network classification of specific audio sources into given categories. Audio sources are represented by various gunshots, from handguns or big bore guns. This article is a follow-up to an existing system for localization of audio sources from security and military areas. The question of successful classification lies in the convenient discrimination of the feature ve...

Classification of emotional speech using spectral pattern features

Speech Emotion Recognition (SER) is a new and challenging research area with a wide range of applications in man-machine interactions. The aim of a SER system is to recognize human emotion by analyzing the acoustics of speech sound. In this study, we propose Spectral Pattern features (SPs) and Harmonic Energy features (HEs) for emotion recognition. These features extracted from the spectrogram ...

classification of emotional speech using spectral pattern features

speech emotion recognition (ser) is a new and challenging research area with a wide range of applications in man-machine interactions. the aim of a ser system is to recognize human emotion by analyzing the acoustics of speech sound. in this study, we propose spectral pattern features (sps) and harmonic energy features (hes) for emotion recognition. these features extracted from the spectrogram ...

Texture classification using spectral histograms

Based on a local spatial/frequency representation,we employ a spectral histogram as a feature statistic for texture classification. The spectral histogram consists of marginal distributions of responses of a bank of filters and encodes implicitly the local structure of images through the filtering stage and the global appearance through the histogram stage. The distance between two spectral his...

Multilevel Spectral Partitioning ofUnstructured