Template adaptation for improving automatic music transcription

In this work, we propose a system for automatic music transcription which adapts dictionary templates so that they closely match the spectral shape of the instrument sources present in each recording. Current dictionary-based automatic transcription systems keep the input dictionary fixed, thus the spectral shape of the dictionary components might not match the shape of the test instrument sources. By performing a conservative transcription pre-processing step, the spectral shape of detected notes can be extracted and utilized in order to adapt the template dictionary. We propose two variants for adaptive transcription, namely for single-instrument transcription and for multiple-instrument transcription. Experiments are carried out using the MAPS and Bach10 databases. Results in terms of multi-pitch detection and instrument assignment show that there is a clear and consistent improvement when adapting the dictionary in contrast with keeping the dictionary fixed.