On Detecting Note Onsets in Piano Music

This paper presents a brief overview of our researches in the use of connectionist systems for transcription of polyphonic piano music and concentrates on the issue of onset detection in musical signals. We propose a new technique for detecting onsets in a piano performance. The technique is based on a combination of a bank of auditory filters, a network of integrateand-fire neurons and a multilayer perceptron. Such structure introduces several advantages over the standard peak-picking onset detection approach and we present its performance on several synthesized and real piano recordings. Results show that our approach represents a viable alternative to existing onset detection algorithms.