Ioannis Karydis

Learn More
This paper presents an algorithm that efficiently retrieves audio data similar to an audio query. The proposed method utilises a feature extraction method for acoustical music sequences. The extracted features are grouped by Minimum Bounding Rectangles (MBRs) and indexed by means of a spatial access method. We also present a novel false alarm resolution(More)
This paper presents a genre classification algorithm for music data. The proposed methodology relies on note pitch and duration features, derived from the repeating terns and duration histograms of a musical piece, respectively. Note-information histograms have a great capability in capturing a fair amount of information regarding harmonic as well as(More)
Listeners are capable to perceive multiple voices in music. Adopting a perceptual view of musical ‘voice’ that corresponds to the notion of auditory stream, a computational model is developed that splits musical scores (symbolic musical data) into different voices. A single ‘voice’ may consist of more than one synchronous notes that are perceived as(More)
Measuring similarity of two musical pieces is an ill-defined problem for which recent research on contextual information, assigned as free-form text (tags) in social networking services, has shown to be highly effective. Nevertheless, approaches based on contextual information require adequate amount of tags per musical datum in order to be effective. In(More)
This paper introduces the problem of discovering maximum-length repeating patterns in music objects. A novel algorithm is presented for the extraction of this kind of patterns from a melody music object. The proposed algorithm discovers all maximum-length repeating patterns using an “aggressive” accession during searching, by avoiding costly repetition(More)
This paper presents a case-study of the effectiveness of a trained system into classifying Greek songs according to their audio characteristics or/and their lyrics into moods. We examine how the usage of different algorithms, featureset combinations and pre-processing parameters affect the precision and recall percentages of the classification process for(More)
Spectral similarity measures have been shown to exhibit good performance in several Music Information Retrieval (MIR) applications. They are also known, however, to possess several undesirable properties, namely allowing the existence of hub songs (songs which frequently appear in nearest neighbor lists of other songs), “orphans” (songs which practically(More)
Social tagging is an increasingly popular phenomenon with substantial impact on Music Information Retrieval (MIR). Tags express the personal perspectives of the user on the music items (such as songs, artists, or albums) they tagged. These personal perspectives should be taken into account inMIR tasks that assess the similarity between music items. In this(More)