A temporally-constrained convolutive probabilistic model for pitch detection
Benetos, E. & Dixon, S. (2011). A temporally-constrained convolutive probabilistic model for pitch detection. In: IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. Applications of Signal Processing to Audio and Acoustics (WASPAA), 2011 IEEE Workshop on, 16 - 19 Oct 2011, New Paltz, NY, US.
Abstract
A method for pitch detection which models the temporal evolution of musical sounds is presented in this paper. The proposed model is based on shift-invariant probabilistic latent component analysis, constrained by a hidden Markov model. The time-frequency representation of a produced musical note can be expressed by the model as a temporal sequence of spectral templates which can also be shifted over log-frequency. Thus, this approach can be effectively used for pitch detection in music signals that contain amplitude and frequency modulations. Experiments were performed using extracted sequences of spectral templates on monophonic music excerpts, where the proposed model outperforms a non-temporally constrained convolutive model for pitch detection. Finally, future directions are given for multipitch extensions of the proposed model.
| Publication Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | M Music and Books on Music > M Music Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Departments: | School of Science & Technology > Computer Science |
Download (121kB) | Preview
Export
Downloads
Downloads per month over past year
Metadata
MetadataActions (login required)
Admin Login