We present a probabilistic model of melodic process in modern Greek church chant. This largely oral tradition often relies on memorization and improvisation skills that are passed on from teacher to student by example, without explicit appeal to rules. The researcher is thus faced with the challenge of inferring the rules of the idiom from a sample corpus of chants. The structure of the rules w...

Musical harmonization of a given melody is a nontrivial problem; slight variations in instrumentation, voicing, texture, and bass rhythm can lead to significant di↵erences in the mood of the resulting piece. This study explores the possibility of automatic musical composition by using machine learning and statistical natural language processing to tailor a piece to a particular mood using an ex...

Three experiments were conducted to study motor programs used by expert singers to produce short tonal melodies. Each experiment involved a response-priming procedure in which singers prepared to sing a primary melody but on 50% of trials had to switch and sing a different (secondary) melody instead. In Experiment 1, secondary melodies in the same key as the primary melody were easier to produc...

This paper describes a method for melody detection in polyphonic musical signals. Our approach starts by obtaining a set of pitch candidates for each time frame, with recourse to an auditory model. Trajectories of the most salient pitches are then constructed. Next, note candidates are obtained by trajectory segmentation (in terms of frequency and pitch salience variations). Too short, lowsalie...

Melody analysis is an important processing step in several areas of Music Information Retrieval (MIR). Processing the pitch values extracted from raw input audio signal may be computationally complex as it requires substantial effort to reduce the uncertainty resulting i.a. from tempo variability and transpositions. A typical example is the melody matching problem in Query-by-Humming (QbH) syst...

The symbolic genre classification algorithm submited to the MIREX (Music Information Retrieval Exchange) 2005 is described here. Our algorithm uses a combination of k-nearest neighbors and Bayesian classifiers trained with different sets of statistical descriptors extracted from melody tracks extracted from MIDI files. It is aimed at classifying melodies by genre. The statistical descriptors de...

The purpose of this study was to determine whether exposure to specific auditory sequences leads to the induction of new motor memories and to investigate the role of the dorsal premotor cortex (dPMC) in this crossmodal learning process. Fifty-two young healthy non-musicians were familiarized with the sound to key-press mapping on a computer keyboard and tested on their baseline motor performan...

Lyrics-to-melody generation is an interesting and challenging topic in AI music research field. Due to the difficulty of learning correlations between lyrics melody, previous methods suffer from low quality lack controllability. Controllability generative models enables human interaction with generate desired contents, which especially important tasks towards human-centered that can facilitate ...