Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This research focuses on the removal of the singing voice in polyphonic audio recordings under real-time constraints. It is based on time-frequency binary masks resulting from the combination of azimuth, phase difference and absolute frequency spectral bin classification and harmonic-derived masks. For the harmonic-derived masks, a pitch likelihood estimation technique based on Tikhonov regularization is proposed. A method for target instrument pitch tracking makes use of supervised timbre models. This approach runs in real-time on off-the-shelf computers with latency below 250ms. The method was compared to a state of the art Non-negative Matrix Factorization (NMF) offline technique and to the ideal binary mask separation. For the evaluation  used a dataset of multi-track versions of professional audio recordings.
['Ricard Marxer', 'Jordi Janer', 'Jordi Bonada']
I am writing a research paper on a idea Low-Latency instrument separation in polyphonic audio using timbre models
[{"from": "human", "value": "I am writing a research paper on a idea Low-Latency instrument separation in polyphonic audio using timbre models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This research focuses on the removal of the singing voice in polyphonic audio recordings under real-time constraints. It is based on time-frequency binary masks resulting from the combination of azimuth, phase difference and absolute frequency spectral bin classification and harmonic-derived masks. For the harmonic-derived masks, a pitch likelihood estimation technique based on Tikhonov regularization is proposed. A method for target instrument pitch tracking makes use of supervised timbre models. This approach runs in real-time on off-the-shelf computers with latency below 250ms. The method was compared to a state of the art Non-negative Matrix Factorization (NMF) offline technique and to the ideal binary mask separation. For the evaluation  used a dataset of multi-track versions of professional audio recordings."}]