Abstract
Separating complex audio sources from a single measurement channel, with no training data, is highly challenging. We introduce a new approach, which relies on the time dynamics of rigid audio models, based on harmonic templates. The velocity vectors of such models are defined and computed in a time-frequency scalogram calculated with a wavelet transform. Similarly to rigid object segmentation in videos, multiple audio sources are discriminated by approximating their velocity vectors with low-dimensional models. The different audio sources are segmented by optimizing a harmonic template selection, which provides piecewise constant velocity approximations. Numerical experiments give examples of blind source separation from single channel audio signals.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
