Delete folder NonSpeech7k with huggingface_hub

NonSpeech7k/info.md

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-# Nonspeech7k Dataset
-
-## Overview
-
-A collection of manually annotated audio files for classification and analysis of human non-speech sounds, designed for academic research on human vocal expressions.
-
-## Source
-
-- **URL**: https://zenodo.org/records/6967442
-- **DOI**: 10.5281/zenodo.6967442
-- **Publication Date**: 2022
-- **Paper**: IET Signal Processing, 2023
-
-## Description
-
-The Nonspeech7k dataset contains 7,014 manually annotated audio files featuring human non-speech sounds. Files range from 500 milliseconds to 4 seconds in duration and are strongly manually annotated with single ground-truth labels.
-
-### Sound Classes
-
-- Breathing
-- Coughing
-- Crying
-- Laughing
-- Screaming
-- Sneezing
-- Yawning
-
-### Original Dataset Statistics
-
-- **Total files**: 7,014
-- **Training set**: 6,289 files
-- **Test set**: 725 files
-- **Original format**: 32kHz, mono WAV
-- **File duration**: 0.5-4 seconds
-- **Total size**: 2.5 GB
-
-### Data Sources
-
-- Freesound.org
-- YouTube
-- Aigei
-
-## Authors
-
-- Muhammad Mamunur Rashid
-- Guiqing Li
-- Chengrui Du
-
-**Affiliation**: South China University of Technology
-
-## License
-
-Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)
-
-**Usage**: Non-commercial and academic research purposes only
-
-## WebDataset Format
-
-| Property | Value |
-|----------|-------|
-| Total Samples | 7,014 |
-| Train | 6,289 samples |
-| Test | 725 samples |
-| Audio Format | FLAC, 48kHz, 16-bit, mono |
-| Metadata Format | JSON with "text" key |
-| Tar Files (train) | 7 |
-| Tar Files (test) | 1 |
-
-## Research Results
-
-- Best model (M12): 79% test accuracy, 0.81 precision, 0.80 F1-score
-- More recent research using CatBoost: 96.21% accuracy
-
-## Citation
-
-If you use this dataset, please cite:
-
-```
-Rashid, M. M., Li, G., & Du, C. (2023).
-Nonspeech7k dataset: Classification and analysis of human non-speech sound.
-IET Signal Processing.
-```

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