Audio Classification
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music
art
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  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.
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  ## Evaluation result
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- <img src="https://www.modelscope.cn/api/v1/models/ccmusic-database/song_structure/repo?Revision=master&FilePath=.%2Fsegment_results.jpg&View=true">
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- ## Download
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- ### By Git
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- ```bash
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- git clone https://www.modelscope.cn/ccmusic-database/song_structure.git
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- pip install modelscope
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- ```
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-
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- ### By API
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  ```python
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  from modelscope import snapshot_download
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  model_dir = snapshot_download('ccmusic-database/song_structure')
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  ```
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  ## Dataset
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  <https://huggingface.co/datasets/ccmusic-database/song_structure>
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  <https://www.modelscope.cn/models/ccmusic-database/song_structure>
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  ## Evaluation
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- <https://github.com/monetjoe/ccmusic_eval/tree/msa>
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-
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- ## Cite
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- ```bibtex
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- @dataset{zhaorui_liu_2021_5676893,
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- author = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han},
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- title = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research},
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- month = {mar},
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- year = {2024},
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- publisher = {HuggingFace},
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- version = {1.2},
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- url = {https://huggingface.co/ccmusic-database}
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- }
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- ```
 
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  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.
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  ## Evaluation result
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+ ![](https://www.modelscope.cn/models/ccmusic-database/song_structure/resolve/master/segment_results.jpg)
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+ ## Usage
 
 
 
 
 
 
 
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  ```python
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  from modelscope import snapshot_download
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  model_dir = snapshot_download('ccmusic-database/song_structure')
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  ```
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+ ## Maintenance
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+ ```bash
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+ git clone git@hf.co:ccmusic-database/song_structure
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+ cd song_structure
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+ ```
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+
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  ## Dataset
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  <https://huggingface.co/datasets/ccmusic-database/song_structure>
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  <https://www.modelscope.cn/models/ccmusic-database/song_structure>
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  ## Evaluation
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+ <https://github.com/monetjoe/ccmusic_eval/tree/msa>