Faucet vs noise

Task: Audio Classification

License: Apache 2.0

Dataset Screenshot

Description

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.

Compatible Blocks

• Feature extraction: Audio (MFE), Spectrogram, Raw Data

• Learning block: Classification

Not sure what to choose? Try out this dataset with the EON Tuner.

Dataset Details

• Total Data Items: 18

• Total Data Length: 0h 15m 40s

• Axis Summary: audio

• Labeling Method: single label

• Train/Test Split: 88.89% / 11.11%

	Training Set	Testing Set
Total Data Items	16	2
Labels	faucet, noise	faucet, noise
Total Data Length	0h 13m 40s	0h 2m 0s

Usage

• Clone the public project.

  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.

• Download

  • Direct link

  • HuggingFace - Soon

  • Kaggle - Soon

• 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:

  • Studio uploader

  • CLI uploader

  • CSV Wizard

  • Python SDK

  • Ingestion API

  • Import from S3 buckets

  • Upload portals (Enterprise feature)

Citation

If you use this dataset in your research paper, please cite it using the following BibTeX:

@misc{edgeimpulse_dataset_497635,
    title = {Audio Classification - Faucet vs noise},
    author = {Edge Impulse},
    year = {2024},
    url = {https://studio.edgeimpulse.com/public/497635/latest},
    note = {Apache 2.0}
}