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--- |
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dataset_info: |
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features: |
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- name: audio |
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dtype: audio |
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- name: username |
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dtype: string |
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- name: Processes |
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dtype: string |
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- name: PulseTypology |
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dtype: string |
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- name: Complexity |
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dtype: string |
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- name: Onset |
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dtype: string |
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- name: Offset |
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dtype: string |
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- name: Type |
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dtype: string |
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- name: MassType |
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dtype: string |
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- name: Direction |
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dtype: string |
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- name: description |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 1918141228 |
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num_examples: 788 |
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download_size: 1608587794 |
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dataset_size: 1918141228 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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license: cc-by-4.0 |
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task_categories: |
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- text-to-audio |
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- audio-classification |
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language: |
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- en |
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size_categories: |
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- n<1K |
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--- |
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|
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The SCHAEFFER dataset (Spectro-morphogical Corpus of Human-annotated Audio with Electroacoustic Features for Experimental Research), is a compilation of 788 raw audio data accompanied by human annotations and morphological acoustic features. |
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The audio files adhere to the concept of Sound Objects introduced by Pierre Scaheffer, a framework for the analysis and creation of sound that focuses on its typological and morphological characteristics. |
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Inside the dataset, the annotation are provided in the form of free text, while the labels are pre-chosen from a list of classes, making the sound description fit into a suitable framework for digital analysis. |
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All the sounds within the dataset are under a "CC-By-4.0-attribution" license. |
