학술논문

Toward a High Performance Piano Practice Support System for Beginners
Document Type
Conference
Source
2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2018. :73-79 Nov, 2018
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Signal Processing and Analysis
Timing
Rhythm
Data mining
Information retrieval
Performance evaluation
Language
ISSN
2640-0103
Abstract
In piano learning, it is difficult especially for beginners to judge by themselves whether their musical performances are appropriate in terms of rhythm and melody. Therefore, we have been developing a piano practice support system, which enables piano beginners to conduct independent practice without their instructors. In this paper, we propose the system with the aid of a deep learning technique: Long Short-Term Memory (LSTM). Our system accepts raw piano sounds, extracting performance information. From these information, we evaluate performance. We evaluated the scheme using actual beginners' performances, and found the proposed system achieved better than previous conventional methods. This paper also presents an application employing our methods. Through subjective evaluation experiments for the proposed application, it turns out almost the all beginners found reflection points, and they maintained their motivation for independent practice.