Meter2800
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'ContextMusic enthusiasts have been trying for a long time to understand how to determine the time signature of any music track and what differentiates one song from another in terms of the rhythmic characteristics. This data hopefully can give the opportunity to do just that.Content: A collection of zipped files. FMA.tar.gz for FMA-medium dataset, MAG.tar.gz for MagnaTagATune dataset, OWN.tar.gz for audio files curated by the authors. The GTZAN dataset was also used in this annotation process but has been excluded in the content because it can be downloaded from   Kaggle. 4 CSV files - Containing train and test data annotations of the audio files performed by a professional musician. The au' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Music Time Signature"]} <|eot_id|>
 Here is the Description of a dataset. Description:'ContextMusic enthusiasts have been trying for a long time to understand how to determine the time signature of any music track and what differentiates one song from another in terms of the rhythmic characteristics. This data hopefully can give the opportunity to do just that.Content: A collection of zipped files. FMA.tar.gz for FMA-medium dataset, MAG.tar.gz for MagnaTagATune dataset, OWN.tar.gz for audio files curated by the authors. The GTZAN dataset was also used in this annotation process but has been excluded in the content because it can be downloaded from   Kaggle. 4 CSV files - Containing train and test data annotations of the audio files performed by a professional musician. The au' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
ContextMusic enthusiasts have been trying for a long time to understand how to determine the time signature of any music track and what differentiates one song from another in terms of the rhythmic characteristics. This data hopefully can give the opportunity to do just that.Content: A collection of zipped files. FMA.tar.gz for FMA-medium dataset, MAG.tar.gz for MagnaTagATune dataset, OWN.tar.gz for audio files curated by the authors. The GTZAN dataset was also used in this annotation process but has been excluded in the content because it can be downloaded from   Kaggle. 4 CSV files - Containing train and test data annotations of the audio files performed by a professional musician. The au
Music Time Signature