Yoonchang Han

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Identifying musical instruments in polyphonic music recordings is a challenging but important problem in the field of music information retrieval. It enables music search by instrument, helps recognize musical genres, or can make music transcription easier and more accurate. In this paper, we present a convolutional neural network framework for predominant(More)
In recent years, neural network approaches have shown superior performance to conventional hand-made features in numerous application areas. In particular, convolutional neural networks (ConvNets) exploit spatially local correlations across input data to improve the performance of audio processing tasks, such as speech recognition, musical chord(More)
Music lessons are a repetitive process of giving feedback on a student’s performance techniques. The manner in which performance skills are improved depends on the particular instrument, and therefore, it is important to consider the unique characteristics of the target instrument. In this paper, we investigate the common mistakes of beginner flute players(More)
Feature learning for music applications has recently received considerable attention from many researchers. This paper reports on the sparse feature learning algorithm for musical instrument identification, and in particular, focuses on the effects of the frame sampling techniques for dictionary learning and the pooling methods for feature aggregation. To(More)
This paper proposes a musical performance feedback system based on real-time audio-score alignment for musical instrument education of beginner musicians. In the proposed system, we do not make use of symbolic data such as MIDI, but acquire a real-time audio input from on-board microphone of smartphone. Then, the system finds onset and pitch of the note(More)
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