Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Entire DC Network
Towards Effective Content-Based Music Retrieval With Multiple Acoustic Feature Composition, Jialie Shen, John Shepherd, Ngu Ahh
Towards Effective Content-Based Music Retrieval With Multiple Acoustic Feature Composition, Jialie Shen, John Shepherd, Ngu Ahh
Research Collection School Of Computing and Information Systems
In this paper, we present a new approach to constructing music descriptors to support efficient content-based music retrieval and classification. The system applies multiple musical properties combined with a hybrid architecture based on principal component analysis (PCA) and a multilayer perceptron neural network. This architecture enables straightforward incorporation of multiple musical feature vectors, based on properties such as timbral texture, pitch, and rhythm structure, into a single low-dimensioned vector that is more effective for classification than the larger individual feature vectors. The use of supervised training enables incorporation of human musical perception that further enhances the classification process. We compare …
The Sonic Representation Of Mathematical Data, Charlie Cullen
The Sonic Representation Of Mathematical Data, Charlie Cullen
Doctoral
Conveying data and information using non-speech audio is an ever growing field of research. Existing work has been performed investigating sonfication and its applications, and this research seeks to build upon these ideas while also suggesting new areas of potential. In this research, initial work focused on the sonification of DNA and RNA nucleotide base sequences for analysis. A case study was undertaken into the potential of rhythmic parsing of such data sequences, with test results indicating that a more effective method of representing data in a sonification was required. Sonification of complex data such as DNA and RNA was …