Project is live at : UrbanSound8k
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paste below code in cmd
git clone https://github.com/BhavyBansal24/UrbanSound8k.git docker build -t ultra_sound8k . docker run -dp 8501:8501 --name SoundDetect ultra_sound8k timeout 2 /nobreak && start http://localhost:8501
- Click here
- Click on Browse Files
- Upload a (.wav) audio file, Model will classify your uploaded sound from the classes.
- classes are : ['dog_bark' , 'children_playing' , 'car_horn' , 'air_conditioner' , 'street_music' , 'gun_shot' , 'siren' , 'engine_idling' , 'jackhammer' , 'drilling']
- After uploading completes, you can see the prediction on right side as shown below
- Below that you can also view other analysis such as spectrogram, Harmonic Percussive Separation, Mel-Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate and many more.
- Dataset is taken from kaggle and link for dataset is here
- This dataset contains 8732 labeled sound of urban sounds from 10 classes: air_conditioner, car_horn, children_playing, dog_bark, drilling, enginge_idling, gun_shot, jackhammer, siren, and street_music
- Link to my kaggle notebook is here
- Do upvote notebook, Hope you like it.
- and do Not forgot to check my other notebooks on kaggle as well
- Hope you love to know more about me, check my Portfolio Website here