Audio Classification
English
music
art

Intro

Our evaluation methodology adopted the approach for structural segmentation evaluation outlined in the Harmonix set, which employed Structural Features for boundary identification, and 2D-Fourier Magnitude Coefficients (2D-FMC) for segment labeling based on acoustic similarity. CQT features serve as input features for the algorithm. The algorithm is implemented using Music Structure Analysis Framework (MSAF). For evaluation metrics, the F-measure is reported for the following metrics: Hit Rate with 0.5 and 3-second windows for boundary retrieval, Pairwise Frame Clustering and Entropy Scores for segment labeling. The evaluation is implemented using mir_eval.

Usage

from modelscope import snapshot_download
model_dir = snapshot_download("ccmusic-database/song_structure")

Maintenance

git clone [email protected]:ccmusic-database/song_structure
cd song_structure

Dataset

https://huggingface.co/datasets/ccmusic-database/song_structure

Mirror

https://www.modelscope.cn/models/ccmusic-database/song_structure

Evaluation

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Dataset used to train ccmusic-database/song_structure