The Spiral Array: An Algorithm for Determining Key Boundaries
ICMAI '02 Proceedings of the Second International Conference on Music and Artificial Intelligence
A System for Automatic Chord Transcription from Audio Using Genre-Specific Hidden Markov Models
Adaptive Multimedial Retrieval: Retrieval, User, and Semantics
Model-based cover song detection via threshold autoregressive forecasts
Proceedings of 3rd international workshop on Machine learning and music
Note recognition from monophonic audio: a clustering approach
AMR'09 Proceedings of the 7th international conference on Adaptive multimedia retrieval: understanding media and adapting to the user
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Automatic Chord Estimation from Audio: A Review of the State of the Art
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Hi-index | 0.00 |
We propose a novel method for detecting changes in the harmonic content of musical audio signals. Our method uses a new model for Equal Tempered Pitch Class Space. This model maps 12-bin chroma vectors to the interior space of a 6-D polytope; pitch classes are mapped onto the vertices of this polytope. Close harmonic relations such as fifths and thirds appear as small Euclidian distances. We calculate the Euclidian distance between analysis frames n +1 and n -1 to develop a harmonic change measure for frame n. A peak in the detection function denotes a transition from one harmonically stable region to another. Initial experiments show that the algorithm can successfully detect harmonic changes such as chord boundaries in polyphonic audio recordings.