Music Onset Detection Using Convolutional Neural Network

Abstract

Onset detection is a primary task in audio processing for any higher-level audio processing such as music information retrieval (MIR) or automatic speech recognition (ASR). Onset detection using data driven approach is hard due to labeled data scarcity. In this work we use some in build dataset for training our convolutional neural network (CNN) work and make some test data for Nepalese traditional music. The CNN with raw waveform of input audio signal performs well in this study for onset detection. This network performs well in diversified audio type where 50 millisecond windows are set in each audio file to identify the presence or absence of onset.