Datasetpublic

MahiA/TUT2017

TUT2017 This is an audio classification dataset for Acoustic Scene Classification. Classes = 15   ,   Split = four-fold Structure audios folder contains audio files. csv_files folder contains CSV files for four-fold cross-validation. To perform cross-validation on fold 1, train_1.csv will be used for the training split and test_1.csv for the testing split, with the same pattern followed for the other folds. To perform training and testing… See the full description on the dataset page: https://huggingface.co/datasets/MahiA/TUT2017.

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Dataset Card

TUT2017

This is an audio classification dataset for Acoustic Scene Classification.

Classes = 15   ,   Split = four-fold

Structure

—audios folder contains audio files.
—csv_files folder contains CSV files for four-fold cross-validation.
—To perform cross-validation on fold 1, train_1.csv will be used for the training split and test_1.csv for the testing split, with the same pattern followed for the other folds.
—To perform training and testing witout cross-validation, use csv_files/train.csv and csv_files/test.csv files respectively.

Download

python

import os
import huggingface_hub
audio_datasets_path = "DATASET_PATH/Audio-Datasets"
if not os.path.exists(audio_datasets_path): print(f"Given {audio_datasets_path=} does not exist. Specify a valid path ending with 'Audio-Datasets' folder.")
huggingface_hub.snapshot_download(repo_id="MahiA/TUT2017", repo_type="dataset", local_dir=os.path.join(audio_datasets_path, "TUT2017"))

Acknowledgment

This dataset is a slightly processed/restructured version of data originally released by Source.<br> Please refer to the respective source for their licensing details and any additional information.

Contact

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