We introduce a novel playlist generation algorithm that focuses on the quality of transitions using a recurrent neural network (RNN). The proposed model assumes that optimal transitions between tracks can be modelled and predicted by internal transitions within music tracks. We introduce modelling sequences of high-level music descriptors using RNNs and discuss an experiment involving different...

This paper presents a method for discovering patterns of note collections that repeatedly occur in a piece of music. We assume occurrences of these patterns must appear at least twice across a musical work and that they may contain slight differences in harmony, timbre, or rhythm. We describe an algorithm that makes use of techniques from the music information retrieval task of music segmentati...

Electromagnetic (EM) noise field distributions measured externally around electrical and electronic equipment have been used for localization and identification of the noise sources inside the equipment. For high frequencies (more than hundreds of MHz), the EM sources at finite distances have been localized by applying the techniques such as MUSIC [1], SPM [2], and holographic imaging [3], to t...

Many aspects of computer-based music notation have been previously discussed. The presented thesis deals with the process of converting a textual description of music into a conventional musical score that can be either printed or viewed on a computer screen. The chosen textual music representation language is GUIDO Music Notation, an adequate, human-readable format, which has been developed si...

Many robot dances are preprogrammed by choreographers for a particular piece of music so that the motions can be smoothly executed and synchronized to the music. We are interested in automating the task of robot dance choreography to allow robots to dance without detailed human planning. Robot dance movements are synchronized to the beats and reflect the emotion of any music. Our work is made u...

Music transcription has been a longtime challenging task even for human. It takes a significant amount of time and effort for an experienced musician to listen to a song or music and transcribe it into music sheets. Automatic Music Transcription (AMT) automates the process of transcribing musics and plays an important role in music information retrieval(MIR). Even though the research for AMT is...

This paper studies the problem of transposition and time-scale invariant (ttsi) polyphonic music retrieval in symbolically encoded music. In the setting, music is represented by sets of points in plane. We give two new algorithms. Applying a search window of size w and given a query point set, of size m, to be searched for in a database point set, of size n, our algorithm for exact ttsi occurre...

A singing voice separation system is a hard yet popular task in the field of music information retrieval (MIR). If successfully separated, a number of algorithms can be applied to vocal melody for any possible application. In this study, we applied a pitch estimation algorithm after separating a singing voice from background music based on the implementation of REPET [1]. Then we evaluated our ...

This report describes the digital humanities project on music similarity. The project is a collaboration between the University of Amsterdam and audio software company Elephantcandy. The project’s aim was to investigate timbre and rhythm similarity and to develop an application that finds similar segments of music. In this report three models are described, one for structural segmentation, one ...

Two techniques are proposed to alleviate the computational burden of MUltiple SIgnal Classification (MUSIC) algorithm applied to Electroencephalogram (EEG) source localization. A significant reduction was achieved by parsing the cortex surface into smaller regions and nominating only a few regions for the exhaustive search inherent in the MUSIC algorithm. The nomination procedure involves a dic...