Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

T. Lidy, A. Rauber, A. Pertusa, J. Iñesta:
"Improving Genre Classification by Combination of Audio and Symbolic Descriptors Using a Transcription System";
Vortrag: International Conference on Music Information Retrieval (ISMIR), Vienna, Austria; 23.09.2007 - 27.09.2007; in: "Proceedings of the 8th International Conference on Music Information Retrieval", S. Dixon, D. Bainbridge, R. Typke (Hrg.); Österreichische Computer Gesellschaft, (2007), ISBN: 978-3-85403-218-2; S. 61 - 66.

Kurzfassung englisch:
Recent research in music genre classification hints at a
glass ceiling being reached using timbral audio features.
To overcome this, the combination of multiple different
feature sets bearing diverse characteristics is needed. We
propose a new approach to extend the scope of the features:
We transcribe audio data into a symbolic form using
a transcription system, extract symbolic descriptors from
that representation and combine them with audio features.
With this method, we are able to surpass the glass ceiling
and to further improve music genre classification, as
shown in the experiments through three reference music
databases and comparison to previously published performance

audio feature extraction, symbolic descriptors, genre classification, transcription, MIDI

Elektronische Version der Publikation:

Erstellt aus der Publikationsdatenbank der Technischen Universitšt Wien.