Amélie Anglade
Biographic Data
| ID | 2787883 |
|---|---|
| NAME | Amélie Anglade |
| GIVEN NAMES | Amélie |
| FAMILY NAME | Anglade |
| SIGNATURE | ANGLADE A |
| AFFILIATIONS | Queen Mary University of London |
| VERIFIED | No |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2010 |
| H-INDEX | 0 |
Improving Music Genre Classification Using Automatically Induced Harmony Rules
We present a new genre classification framework using both low-level signal-based features and high-level harmony features. A state-of-the-art statistical genre classifier based on timbral features is extended using a first-order random forest containing for each genre rules derived from harmony or chord sequences. This random forest has been automatically induced, using the first-order logic induction algorithm TILDE, from a dataset, in which fo…
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Improving Music Genre Classification Using Automatically Induced Harmony Rules
We present a new genre classification framework using both low-level signal-based features and high-level harmony features. A state-of-the-art statistical genre classifier based on timbral features is extended using a first-order random forest containing for each genre rules derived from harmony or chord sequences. This random forest has been automatically induced, using the first-order logic induction algorithm TILDE, from a dataset, in which fo…
Art (1 work) · Artificial Intelligence (1 work) · Computer Science (1 work) · Feature vector (1 work) · Harmony search (1 work) · Machine learning (1 work) · Music and Audio Processing (1 work) · Music Technology and Sound Studies (1 work) · Natural language processing (1 work) · Random forest (1 work)