Enhanced peak picking for onset detection with recurrent neural networks
نویسندگان
چکیده
We present a new neural network based peak-picking algorithm for common onset detection functions. Compared to existing handcrafted methods it yields a better performance and leads to a much lower number of false negative detections. The performance is evaluated on basis of a huge dataset with over 25k annotated onsets and shows a significant improvement over existing methods in cases of signals with previously unknown levels.
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