Task: Audio Classification
License: Apache 2.0
This dataset has been collected by Edge Impulse teams to recognize the sound of water running from a faucet, even in the presence of other background noise.
You can also follow our tutorial learn how to collect audio data from microphones, use signal processing to extract the most important information, and train a deep neural network that can tell you whether the sound of running water can be heard in a given clip of audio. Finally, you'll deploy the system to an embedded device and evaluate how well it works.
Feature extraction: Audio (MFE), Spectrogram, Raw Data
Learning block: Classification
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Total Data Items: 18
Total Data Length: 0h 15m 40s
Axis Summary: audio
Labeling Method: single label
Train/Test Split: 88.89% / 11.11%
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To clone and use this project, visit the Edge Impulse Studio link, click on the Clone button on the top-right corner and follow the cloning instructions.
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Import this dataset to your Edge Impulse project
This project uses the Edge Impulse Exporter Format (info.labels). See this documentation page for more info.
Edge Impulse also supports different data sample formats and dataset annotation formats that you can import into your project to build your edge AI models:
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Training Set
Testing Set
Total Data Items
16
2
Labels
faucet, noise
faucet, noise
Total Data Length
0h 13m 40s
0h 2m 0s