38 resultados para Christmas music.
Resumo:
The present study investigates the relation of perceived arousal (continuous self-rating), autonomic nervous system activity (heart rate, heart rate variability) and musical characteristics (sound intensity, musical rhythm) upon listening to a complex musical piece. Twenty amateur musicians listened to two performances of Chopin's "Tristesse" with different rhythmic shapes. Besides conventional statistical methods for analyzing psychophysiological reactions (heart rate, respiration rate) and musical variables, semblance analysis was used. Perceived arousal correlated strongly with sound intensity; heart rate showed only a partial response to changes in sound intensity. Larger changes in heart rate were caused by the version with more rhythmic tension. The low-/high-frequency ratio of heart rate variability increased-whereas the high frequency component decreased-during music listening. We conclude that autonomic nervous system activity can be modulated not only by sound intensity but also by the interpreter's use of rhythmic tension. Semblance analysis enables us to track the subtle correlations between musical and physiological variables.
Resumo:
Music plays an important role in the daily life of cochlear implant (CI) users, but electrical hearing and speech processing pose challenges for enjoying music. Studies of unilateral CI (UCI) users' music perception have found that these subjects have little difficulty recognizing tempo and rhythm but great difficulty with pitch, interval and melody. The present study is an initial step towards understanding music perception in bilateral CI (BCI) users. The Munich Music Questionnaire was used to investigate music listening habits and enjoyment in 23 BCI users compared to 2 control groups: 23 UCI users and 23 normal-hearing (NH) listeners. Bilateral users appeared to have a number of advantages over unilateral users, though their enjoyment of music did not reach the level of NH listeners.
Resumo:
Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates.
Khaled Arman at the Music Festival Bern. The Multi-Layered Performance of an Afghan Migrant Identity