dc.contributor.author | Rocher, Thomas | |
dc.contributor.author | Hanna, Pierre | |
dc.contributor.author | Robine, Matthias | |
dc.contributor.author | Conklin, Darrell | |
dc.date.accessioned | 2012-09-14T07:00:13Z | |
dc.date.available | 2012-09-14T07:00:13Z | |
dc.date.issued | 2012 | |
dc.identifier.uri | http://hdl.handle.net/10810/8592 | |
dc.description.abstract | This paper proposes a new method for local key and chord estimation from audio signals. This method relies primarily on principles from music theory, and does not require any training on a corpus of labelled audio files. A harmonic content of the musical piece is first extracted by computing a set of chroma vectors. A set of chord/key pairs is selected for every frame by correlation with fixed chord and key templates. An acyclic harmonic graph is constructed with these pairs as vertices, using a musical distance to weigh its edges. Finally, the sequences of chords and keys are obtained by finding the best path in the graph using dynamic programming. The proposed method allows a mutual chord and key estimation. It is evaluated on a corpus composed of Beatles songs for both the local key estimation and chord recognition tasks, as well as a larger corpus composed of songs taken from the Billboard dataset. | es |
dc.language.iso | eng | es |
dc.relation.ispartofseries | EHU-KZAA-TR;2012-04 | |
dc.rights | info:eu-repo/semantics/openAccess | es |
dc.subject | audio | es |
dc.subject | music information retrieval | es |
dc.subject | harmony | es |
dc.subject | chroma | es |
dc.subject | chord | es |
dc.title | Music-Theoretic Estimation of Chords and Keys from Audio | es |
dc.type | info:eu-repo/semantics/report | es |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | es_ES |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala | es_ES |