Computer-aided Melody Note Transcription Using the Tony Software: Accuracy and Efficiency
| Main Authors: | Matthias Mauch, Chris Cannam, Rachel Bittner, George Fazekas, Justin Salamon, Jiajie Dai, Juan Bello, Simon Dixon |
|---|---|
| Other Authors: | Battier, Marc, Bresson, Jean, Couprie, Pierre, Davy-Rigaux, Cécile, Fober, Dominique, Geslin, Yann, Genevois, Hugues, Picard, François, Tacaille, Alice |
| Format: | Proceeding |
| Terbitan: |
Institut de Recherche en Musicologie
, 2015
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| Online Access: |
https://zenodo.org/record/1289636 |
Daftar Isi:
- We present Tony, a software tool for the interactive evaluation of melodies from monophonic audio recordings, and evaluate its usability and the accuracy of its note extraction method. The scientific study of acoustic performances of melodies, whether sung or played, requires the accurate transcription of notes and pitches. To achieve the desired transcription accuracy for a particular application, researchers manually correct results obtained by automatic methods. Tony is an interactive tool directly aimed at making this correction task efficient. It provides (a) state-of-the art algorithms for pitch and note estimation, (b) visual and auditory feedback for easy error-spotting, (c) an intelligent graphical user interface through which the user can rapidly correct estimation errors, d) extensive export functions enabling further processing in other applications. We show that Tony's built in automatic note transcription method compares favorably against existing tools. We report how long it takes to annotate recordings on a set of 96 recordings and study the effect of piece, the number of edits made and the annotator's increasing mastery of the software. Tony is Open Source software, with source code and compiled binaries for Windows and Mac OS X available from https://code.soundsoftware.ac.uk/projects/tony/.