To listen to the brain activities as a piece of music, we proposed the scale-free brainwave music (SFBM) technology, which translated scalp EEGs into music notes according to the power law of both EEG and music. In the present study, the methodology was extended for deriving a quartet from multi-channel EEGs with artistic beat and tonality filtering. EEG data from multiple electrodes were first...

Introduction: This study aimed to investigate the effect of music on pain, anxiety and vital signs in children undergoing colonoscopy.   Method and Materials: This randomized study was carried out on 101 children (7 to 14 years old) requiring colonoscopy. Children were randomly allocated to a control or case group. The case group was played relaxing music (by Clayderman) during the procedure. S...

Timing plays an important role in the performance and appreciation of almost all types of music. It has been studied extensively in music perception and music performance research (see Palmer 1997 for a review). The most important outcome of this research is that a large part of the timing patterns found in music performance—commonly referred to as expressive timing—can be explained in terms of...

Locating singing voice segments is essential for convenient indexing, browsing and retrieval large music archives and catalogues. Furthermore, it is beneficial for automatic music transcription and annotations. The approach described in this paper usesMel-Frequency Cepstral Coefficients in conjunction with Gaussian Mixture Models for discriminating two classes of data (instrumental music and si...

As mobile devices are always with users and music listening is a very personal and situational behaviour, contextual information could be used to greatly enhance music recommendations. However, making such use of context, while learning user profiles, is still a challenging problem. We present a system for collecting context and usage data from mobile devices, but targeted at recommending music...

In our talk we will present a piano music companion that is able to follow and understand (at least to some extent) a live piano performance. Within a few seconds the system is able to identify the piece that is being played, and the position within the piece. It then tracks the performance over time via a robust score following algorithm. Furthermore, the system continuously re-evaluates its c...

Modeling and Predicting Emotion in Music Erik M. Schmidt Youngmoo E. Kim, Ph.D. With the explosion of vast and easily-accessible digital music libraries over the past decade, there has been a rapid expansion of research towards automated systems for searching and organizing music and related data. Online retailers now offer vast collections of music, spanning tens of millions of songs, availabl...

Familiarity is a crucial factor in music engagement, but very few study focuses on its neural correlates. We investigated effects of familiarity based on electroencephalogram in music-emotion recognition. Our research focused on self-reporting and continuous annotation based on the hypothesis that emotion in music experiencing is subjective and varies over time. Our methodology allowed subject ...

Locative music experiences are often non-linear and as such the final structure of the music heard is guided by the movements of the user. We note an absence of principles regarding how composers should approach the structuring of such locative soundtracks. For instance, how does one compose for a nonlinear soundtrack using linear, pre-composed placed sounds, where fixed musical time is placed ...

We investigated neural correlates of retrieval success for music memory using event-related functional magnetic resonance imaging. To minimize the interference from MRI scan noise, we used sparse temporal sampling technique. Newly composed music materials were employed as stimuli, which enabled us to detect regions in absence of effects of experience with the music stimuli in this study. Whole ...