R. Badeau, B. David, V. Emiya, and Y. Grenier, “Harmonic Plus Noise Decomposition: Time-frequency Reassignment Versus a Subspace Based Method,” in Proc. AES Convention 120, May 2006, Paper 6644. [Online]. Available: https://aes.org/publications/elibrary-page/?id=13448
Badeau R, David B, Emiya V, Grenier Y. Harmonic Plus Noise Decomposition: Time-frequency Reassignment Versus a Subspace Based Method. In: AES Convention 120. Audio Engineering Society; 2006. Paper 6644. Available from: https://aes.org/publications/elibrary-page/?id=13448
@inproceedings{Badeau2006_13448,
author = {Badeau, Roland and David, Bertrand and Emiya, Valentin and Grenier, Yves},
title = {{Harmonic Plus Noise Decomposition: Time-frequency Reassignment Versus a Subspace Based Method}},
booktitle = {AES Convention 120},
note = {Paper 6644},
year = {2006},
month = may,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=13448}
}
TY - CPAPER
TI - Harmonic Plus Noise Decomposition: Time-frequency Reassignment Versus a Subspace Based Method
AU - Badeau, Roland
AU - David, Bertrand
AU - Emiya, Valentin
AU - Grenier, Yves
T2 - AES Convention 120
M1 - Paper 6644
PY - 2006
DA - 2006/05/06
UR - https://aes.org/publications/elibrary-page/?id=13448
PB - Audio Engineering Society
LA - en
AB - This work deals with the Harmonic+Noise decomposition and, as targeted application, to extract transient background noise surrounded by a signal having a strong harmonic content (speech for instance). In that perspective, a method based on the reassigned spectrum and a High Resolution subspace tracker are compared, both on simulations and in a more realistic manner. The reassignment re-localizes the time-frequency energy around a given pair (analysis time index, analysis frequency bin) while the High Resolution method benefits from a characterization of the signal in terms of a space spanned by the harmonic content and a space spanned by the stochastic content. Both methods are adaptive and the estimations are updated from a sample to the next.
ER -