ScholarWorksIndianapolis
  • Communities & Collections
  • Browse ScholarWorks
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    or
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Guan, Hongzhao"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Automatic Piano Fingering Estimation Using Recurrent Neural Networks
    (2021-11) Guan, Hongzhao; Yan, Zhao; Hsu, Timothy; Music and Arts Technology, School of Engineering and Technology
    Deciding piano fingerings is an essential skill for all piano players regardless of their expertise. Traditionally, pianists and piano educators first need to analyze musical scores, then they manually label the fingerings on the scores; however, this process is time-consuming and inefficient. This paper proposes a novel automatic piano fingerings estimating method by utilizing Bidirectional Long Short-term Memory (BI-LSTM) networks — a special type of Recurrent Neural Networks (RNNs). This is one of the first studies to explore the possibilities of applying deep learning to estimate piano fingerings. Together with the new method, a novel input representation is designed to capture the relations between surrounding notes. Furthermore, in addition to directly comparing the estimations with the ground-truth, this paper proposes a novel evaluation metric to assess the playability of the estimated fingerings. The results illustrate the effectiveness of the proposed method that generates playable and accurate estimated fingerings.
About IU Indianapolis ScholarWorks
  • Accessibility
  • Privacy Notice
  • Copyright © 2025 The Trustees of Indiana University