paddleaudio.datasets.esc50 module

class paddleaudio.datasets.esc50.ESC50(mode: str = 'train', split: int = 1, feat_type: str = 'raw', **kwargs)[source]

Bases: AudioClassificationDataset

The ESC-50 dataset is a labeled collection of 2000 environmental audio recordings suitable for benchmarking methods of environmental sound classification. The dataset consists of 5-second-long recordings organized into 50 semantical classes (with 40 examples per class)

Reference:: ESC: Dataset for Environmental Sound Classification http://dx.doi.org/10.1145/2733373.2806390

Methods

meta_info

alias of META_INFO

archieves = [{'url': 'https://paddleaudio.bj.bcebos.com/datasets/ESC-50-master.zip', 'md5': '7771e4b9d86d0945acce719c7a59305a'}]

audio_path = 'ESC-50-master/audio'

label_list = ['Dog', 'Rooster', 'Pig', 'Cow', 'Frog', 'Cat', 'Hen', 'Insects (flying)', 'Sheep', 'Crow', 'Rain', 'Sea waves', 'Crackling fire', 'Crickets', 'Chirping birds', 'Water drops', 'Wind', 'Pouring water', 'Toilet flush', 'Thunderstorm', 'Crying baby', 'Sneezing', 'Clapping', 'Breathing', 'Coughing', 'Footsteps', 'Laughing', 'Brushing teeth', 'Snoring', 'Drinking, sipping', 'Door knock', 'Mouse click', 'Keyboard typing', 'Door, wood creaks', 'Can opening', 'Washing machine', 'Vacuum cleaner', 'Clock alarm', 'Clock tick', 'Glass breaking', 'Helicopter', 'Chainsaw', 'Siren', 'Car horn', 'Engine', 'Train', 'Church bells', 'Airplane', 'Fireworks', 'Hand saw']

meta = 'ESC-50-master/meta/esc50.csv'

meta_info: alias of META_INFO