Tag Archives: Ensemble

Ethnomusicological Enquiry into Contemporary Indigenously Inclined Ìjálá Music in Yoruba Land (Published)

Yoruba social music appeal to traditional audience who are accustomed to the conventional property embedded in it. The appeal facilitates an increasing number of traditionally inclined social music practitioners who are gradually directing their efforts towards the creation of new form of ensemble music. Ethnographic method of data collection used in the study revealed that Ìjálá genre is text-based with symbolic use of words and allusion varying from place to place. It is monophonic in concept and the subject is centered on praise and adoration. It is seen as a verbal tool in the context of Ìjálá performances. The finding reveals the functional process of oral genre from place to place within a family or otherwise. Information on the use of Ìjálá music for different occasions was significant to the study.  It further reveals the healing process of the oral genre.

Keywords: Ensemble, Music, Social, Yoruba, chant, Ìjálá

Melody Analysis for Prediction of the Emotions Conveyed by Sinhala Songs (Published)

This paper describes our attempt of assessing the capability of music melodies in isolation in order to classify music files into different emotional categories in the context of Sri Lankan music. In our approach, Melodies (predominant pitch sequences) are extracted from songs and the feature vectors are created from them which are ultimately subjected to supervised learning approaches with different classifier algorithms and also with classifier accuracy enhancing algorithms. The models we trained didn’t perform well enough to classify songs into different emotions, but they always showed that the melody is an important factor for the classification. Further experiments with melody features along with some non-melody features showed us that those feature combinations perform much better, hence brought us to the conclusion that, even though, the melody plays a major role in differentiating the emotions into different categories, it needs the support of other features too for a proper classification.

Keywords: Emotion Classification, Ensemble, Feature Selection, Melody, Music Information Retrival, Supervised Learning