Glass breaking
Task: Audio Classification
License: BSD 3-Clause Clear
Dataset Screenshot
Description
This dataset has been generated by Edge Impulse teams to recognize the sound of glass breaking. The synthetic data has been generated using the Edge Impulse’s ElevenLabs.io integration. You can also have a look at the blog post That Sounds Great: Create Ultra-Realistic Audio Datasets with ElevenLabs.io.Compatible Blocks
- Feature extraction: Audio (MFE), Spectrogram, Raw Data
- Learning block: Classification
Dataset Details
- Total Data Items: 500
- Total Data Length: 0h 21m 15s
- Axis Summary: audio
- Labeling Method: single label
- Train/Test Split: 80.00% / 20.00%
| Training Set | Testing Set | |
|---|---|---|
| Total Data Items | 400 | 100 |
| Labels | glass_breaking, noise | glass_breaking, noise |
| Total Data Length | 0h 17m 37s | 0h 3m 37s |
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.
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Download
- Direct link
- HuggingFace - Soon
- Kaggle - Soon
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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: