Open KilYep opened 4 months ago
I've tried to train a guitar sep model, but the results are not good, like though bass can reach a nSDR of 10+, but acoustic guitar can only reach about 3
I've tried to train a guitar sep model, but the results are not good, like though bass can reach a nSDR of 10+, but acoustic guitar can only reach about 3
Oh, that's too bad. Is the poor performance of guitar sep models due to the fact that separating different guitars is inherently difficult for algorithms, or is it more of a dataset issue?
❓ Questions
First of all, thank you for the great demucs project! I would like to ask if it is feasible to train a new model using demucs that can separate leading guitar and rhythm guitar, and if this could achieve good results. Because I also understand that separating leading and rhythm guitar seems to be an extremely tricky problem. But if it is feasible, how should such a new model be trained? Should it be trained from scratch or based on existing demucs models like 4stems? Approximately how much time would it take to train a model like this?