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--- |
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datasets: |
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- SHD-2 |
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tags: |
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- audio |
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- audio-classificaiton |
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- shower detection |
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metrics: |
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- Accuracy |
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--- |
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**Context** |
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Most of our great brilliant ideas happen in periods of relaxation, like taking a |
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shower, however, once we leave the shower, we forget the brilliant idea. What if |
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we do not forget, and collect your ideas in the shower? |
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**What is the Shower Ideas concept?** |
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This is an app that detects when someone is taking a shower (douche) and asks |
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“do you have any idea?”, and the person will speak while taking the shower telling |
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the idea. And also will ask questions after taking a shower. |
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**Abstract about the model** |
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This model was trained based on *facebook/wav2vec2-base-960h* (which is a pretrained model on 960 hours of Librispeech on 16kHz sampled speech audio.) in order to classify the audio input into shower or no_shower. |
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**Dataset** |
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The SHD-2 dataset is a labeled collection of 2260 audio recordings of shower and no shower sounds. |
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The dataset consists of 6-second-long recordings organized into 2 classes (with 1130 examples per class). |
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# Usage |
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In order to use the model in your Python script just copy the following code: |
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```python |
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from transformers import pipeline |
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audio_input = 'example.wav' |
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classifier = pipeline("audio-classification", model="abdelhalim/Shower_Sound_Recognition") |
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labels = classifier(audio_input) |
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labels |
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``` |
