An Investigation of feature models for music genre classification using the support vector classifier |
Anders Meng, John Shawe-Taylor
|
| Abstract | The purpose of this work is two-fold:
1. To investigate the multivariate Gaus-
sian model and multivariate autoregressive
model for modelling short time features
(e.g. mel frequency cepstral coefficients)
over a segment of audio.
2. Investigate how these two models can be
formulated in a kernel framework. |
| Keywords | Product probability kernel, Convolution kernel, multivariate autoregressive model, SVM, Support Vector machine |
| Type | Misc [Poster] |
| Journal/Book/Conference | International Conference on Music Information Retrieval |
| Year | 2005 |
| Address | London |
| Note | Poster presented at the conference |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |