Musical Features for Automatic Music Transcription Evaluation
Adrien Ycart, Lele Liu, Emmanouil Benetos, Marcus T. Pearce
TL;DR
This paper introduces specific musical features designed to evaluate automatic music transcription systems, aiming to improve the perceptual relevance of evaluation metrics in piano transcription tasks.
Contribution
It provides a detailed formal description of novel features for assessing the perceptual validity of transcription evaluation metrics.
Findings
Features enhance the perceptual alignment of evaluation metrics
Formal descriptions facilitate implementation and comparison
Supports development of more perceptually meaningful evaluation methods
Abstract
This technical report gives a detailed, formal description of the features introduced in the paper: Adrien Ycart, Lele Liu, Emmanouil Benetos and Marcus T. Pearce. "Investigating the Perceptual Validity of Evaluation Metrics for Automatic Piano Music Transcription", Transactions of the International Society for Music Information Retrieval (TISMIR), Accepted, 2020.
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Taxonomy
TopicsMusic and Audio Processing · Music Technology and Sound Studies · Diverse Musicological Studies