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In this paper we propose a music Query by Humming System made of two main functional blocks; the first implements a voice-to-midi transcription algorithm to process the query, the second implements a search engine based on a novel template matching technique for Dynamic Time Warping. The voice-to-midi algorithm transforms the sung or hummed query in a MIDI file by segmenting and identifying the notes'...
An automatic procedure, based on a genetic algorithm capable of optimizing a diagnostic system for the recognition and identification of partial-discharge (PD) pulse patterns in the terminations and joints of solid dielectric extruded power distribution cables, is described. The core of the diagnostic system is a fuzzy neural network, namely a Min-Max classifier. The genetic optimization is capable...
This paper deals with the musical genre classification problem, starting from a set of features extracted directly from MPEG-1 layer III compressed audio data. The automatic classification of compressed audio signals into a short hierarchy of musical genres is explored. More specifically, three feature sets for representing timbre, rhythmic content and energy content are proposed for a four leafs...
An automatic classification system coping with graph patterns with node and edge labels belonging to continuous vector spaces is proposed. An algorithm based on inexact matching techniques is used to discover recurrent subgraphs in the original patterns, the synthesized prototypes of which are called symbols. Each original graph is then represented by a vector signature describing it in terms of the...
This paper deals with the Music/Speech classification problem, starting from a set of features extracted directly from compressed audio data. The proposed classification system is able to label audio sequences stored as compressed MPEG layer III files. Decoding and analyzing in a unique stage is a fundamental tool for audio streaming applications, such as real time classification. Moreover, the techniques...
In this paper we propose an image classification system able to solve automatically a large set of problem instances by a granular computing approach. By means of a watershed segmentation algorithm, each image is decomposed into a set of segments (information granules), characterized by suited color, texture and shape features (segment signature). Successively, images are represented by a symbolic...
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