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Intelligent Installation Design and Implementation of Automatic Performative Transcription for Plucked String Instrument

Published:23 April 2024Publication History

ABSTRACT

Since the 20th century, synthesizers and MIDI keyboards offer composers more convenient operation and a higher creative ceiling. However, traditional Chinese plucked instruments like the Pipa have only just begun to explore the realms of electronic music and automatic notation. This study focuses on the Pipa as the subject, aiming to design and implement a device that captures performance-related data while maintaining the original conditions of the instrument, and automatically transcribes this data into musical notation.This study presents a data collection module based on Arduino hardware. This design involves detection by making certain modifications to the instrument and connecting wires to the instrument's frets which achieves real-time detection of the performer's finger movements via a hardware loop, collecting performance data for transcription. This setup allows performer to record and preserve details of their performance, including the fingering and string values for each note played. Through extensive research on sensors and underlying theories, this study has essentially achieved an intelligent device for the automatic notation of plucked instrument performances. Furthermore, with further refinements, it can also be applied to more complex,technically rich musical compositions and more instruments in the future.

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  1. Intelligent Installation Design and Implementation of Automatic Performative Transcription for Plucked String Instrument

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    • Published in

      cover image ACM Other conferences
      ICCIP '23: Proceedings of the 2023 9th International Conference on Communication and Information Processing
      December 2023
      648 pages
      ISBN:9798400708909
      DOI:10.1145/3638884

      Copyright © 2023 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 23 April 2024

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      Overall Acceptance Rate61of301submissions,20%
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