I think the model is designed and trained with a hop size of 480 samples. What is the best way to use the model in a setup where the frame size is forced to be e.g. 1024 samples? Just put buffers around the model and process chunks of 480 samples or would it be better to change the hop size of the model? But if the hop size of the model is changed, do we have to retrain it?
I think the model is designed and trained with a hop size of 480 samples. What is the best way to use the model in a setup where the frame size is forced to be e.g. 1024 samples? Just put buffers around the model and process chunks of 480 samples or would it be better to change the hop size of the model? But if the hop size of the model is changed, do we have to retrain it?
Thanks