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manfye/baby-cry-detector
baby-cry-detector is a audio classification model from manfye. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for onnxruntime. The card lists the license as cc-by-sa-4.0.
Experimental quality-filtered compact CNN v0.2 for binary cry versus noncry classification. The ONNX file is used by the local Next.js demo.
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From the Hugging Face model README
Experimental quality-filtered compact CNN v0.2 for binary cry versus non_cry classification. The ONNX file is used by the local Next.js demo.
model-metadata.json| Evaluation set | Files | Accuracy | Balanced accuracy | Macro-F1 | Cry recall |
|---|---|---|---|---|---|
| Development validation | 207 | 99.52% | 98.96% | 99.32% | — |
| Regression partition | 204 | 97.06% | 95.19% | 95.85% | — |
| Enes cry-only probe | 294 | — | — | — | 97.28% |
The Enes probe contains only cry-positive examples, so its recall is not full classification accuracy. These are dataset-level evaluation results, not independent real-world validation.
This model is for experimentation only. It must not be used for medical diagnosis, safety monitoring, or deciding whether an infant needs care. The score describes one processed clip and is not the model's overall accuracy.
The model artifact and repository-authored documentation are released under Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0). No training audio is included. This license does not relicense third-party datasets; downstream users remain responsible for the original dataset terms and unresolved lineage.