1. J.M. Iñesta and C. Pérez-Sancho

, vol. Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2013), pp. 211-215. Vancouver, Canada (2013)

Automatic music transcription has usually been performed as an autonomous task and its evaluation has been made in terms of precision, recall, accuracy, etc. Nevertheless, in this work, assuming that the state of the art is far from being perfect, it is considered as an interactive one, where an expert user is assisted in its work by a transcription tool. In this context, the performance evaluation of the system turns into an assessment of how many user interactions are needed to complete the work. The strategy is that the user interactions can be used by the system to improve its performance in an adaptive way, thus minimizing the workload. Also, a multimodal approach has been implemented, in such a way that different sources of information, like onsets, beats, and meter, are used to detect notes in a musical audio excerpt. The system is focused on monotimbral polyphonic transcription.