Audio-aligned jazz harmony dataset for automatic chord transcription and corpus-based research

TitleAudio-aligned jazz harmony dataset for automatic chord transcription and corpus-based research
Publication TypeConference Paper
Year of Publication2018
Conference NameInternational Society for Music Information Retrieval Conference
AuthorsEremenko, V., Demirel E., Bozkurt B., & Serra X.
Conference Start Date23/09/2018
Conference LocationParis
AbstractIn this paper we present a new dataset of time-aligned jazz harmony transcriptions. This dataset is a useful resource for content-based analysis, especially for training and evaluating chord transcription algorithms. Most of the available chord transcription datasets only contain annotations for rock and pop, and the characteristics of jazz, such as the extensive use of seventh chords, are not represented. Our dataset consists of annotations of 113 tracks selected from “The Smithsonian Collection of Classic Jazz” and “Jazz: The Smithsonian Anthology,” covering a range of performers, subgenres, and historical periods. Annotations were made by a jazz musician and contain information about the meter, structure, and chords for entire audio tracks. We also present evaluation results of this dataset using stateof- the-art chord estimation algorithms that support seventh chords. The dataset is valuable for jazz scholars interested in corpus-based research. To demonstrate this, we extract statistics for symbolic data and chroma features from the audio tracks.
preprint/postprint documenthttps://doi.org/10.5281/zenodo.1291834
intranet