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README.md
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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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---
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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.
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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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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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| 48 |
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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| 49 |
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.
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