Vous avez un workflow ComfyUI ? Obtenez une documentation lisible directement dans votre navigateur.Rendre un workflow lisible.Essayer maintenant ↗
An Audio Spectrogram Transformer (AST) model fine-tuned on the ESC-50 dataset for environmental sound classification.
Source du modèle
Description de la source
An Audio Spectrogram Transformer (AST) model fine-tuned on the ESC-50 dataset for environmental sound classification.
This model is based on the Audio Spectrogram Transformer architecture, fine-tuned to classify 50 categories of environmental sounds. The AST applies a pure attention mechanism to audio spectrograms, treating them as sequences of patches similar to Vision Transformers (ViT).
Sources
1 sourceVérifié 19 sept.
Artefacts du modèle
1 artefactExtraits de sources
2 extraitsThe model classifies audio into 50 environmental sound categories:
Animals: cat, chirping_birds, cow, crow, dog, frog, hen, insects, pig, rooster, sheep
Natural Sounds: crackling_fire, crickets, rain, sea_waves, thunderstorm, water_drops, wind
Human Sounds: breathing, brushing_teeth, clapping, coughing, crying_baby, drinking_sipping, footsteps, laughing, sneezing, snoring
Domestic Sounds: clock_alarm, clock_tick, door_wood_creaks, door_wood_knock, glass_breaking, keyboard_typing, mouse_click, toilet_flush, vacuum_cleaner, washing_machine
Urban Sounds: airplane, car_horn, church_bells, engine, fireworks, helicopter, siren, train
Mechanical/Tools: can_opening, chainsaw, hand_saw, pouring_water
BSD-3-Clause
--- license: bsd-3-clause tags: - audio-classification - audio - environmental-sound datasets: - ashraq/esc50 pipeline_tag: audio-classification base_model: MIT/ast-finetuned-audioset-10-10-0.4593 --- # AST Fine-tuned on ESC-50 An Audio Spectrogram Transformer (AST) model fine-tuned on the ESC-50 dataset for environmental sound classification. ## Model Description This model is based on the [Audio Spectrogram Transformer](https://arxiv.org/abs/2104.01778) architecture, fine-tuned to classify 50 categories of environmental sounds. The AST applies a pure attention mechanism to audio spectrograms, treating them as sequences of patches similar to Vision Transformers (ViT). ## Training - **Base Model**: MIT/ast-finetuned-audioset-10-10-0.4593 - **Dataset**: [ESC-50](https://github.com/karolpiczak/ESC-50) (Environmental Sound Classification) ## Labels The model classifies audio into 50 environmental sound categories: **Animals**: cat, chirping_birds, cow, crow, dog, frog, hen, insects, pig, rooster, sheep **Natural Sounds**: crackling_fire, crickets, rain, sea_waves, thunderstorm, water_drops, wind **Human Sounds**: breathing, brushing_teeth, clapping, coughing, crying_baby, drinking_sipping, footsteps, laughing, sneezing, snoring **Domestic Sounds**: clock_alarm, clock_tick, door_wood_creaks, door_wood_knock, glass_breaking, keyboard_typing, mouse_click, toilet_flush, vacuum_cleaner, washing_machine **Urban Sounds**: airplane, car_horn, church_bells, engine, fireworks, helicopter, siren, train **Mechanical/Tools**: can_opening, chainsaw, hand_saw, pouring_water ## License BSD-3-Clause
Source context: 68 downloads · 2 likes · Pipeline audio-classification · Repo bioamla/ast-esc50
