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# Infant Cry Detection Dataset — 50+ Hours of Real Baby Cry Audio
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**50+ hours of real infant cry recordings** for training infant cry detection, cry classification, and sound event detection models. Manually verified files captured in natural domestic conditions, with per-file metadata on location, background noise, and recording device
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## Contact us and share your feedback — receive additional samples for free! 😊
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## Key Highlights
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- **50+ hours** of real-world infant cry audio
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- **Manually verified**
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- **Authenticity filter applied** — files resembling internet downloads removed
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- **Indoor + outdoor** capture conditions
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- **Background noise variation**
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- **No synthetic audio, no augmentation, no AI-generated content**
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- Smartphone-first recordings (matches baby monitor deployment conditions)
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- **Commercial license available**
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## Use This Dataset For
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- **Infant cry detection**
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- **Sound event detection (SED)**
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- **Sleep tracking applications**
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- **Cry-aware smart home automation**
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- **Parental support apps**
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- **Audio classification research**
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## Dataset Structure
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```
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infant-cry-detection-dataset/
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├── audio/
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│ ├── cry_00001.wav
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│ ├── cry_00002.m4a
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│ └── ... (WAV + M4A files)
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├── metadata.csv
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└── README.md
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```
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### metadata.csv schema
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| Field | Type | Values |
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|-------|------|--------|
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| `record_id` | string | unique recording ID |
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| `file_name` | string | path to audio file |
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| `file_ext` | string | .wav, .m4a |
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| `duration_sec` | float | 10–100 seconds |
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| `sample_rate_hz` | int | 48000 (majority), 44100, 16000 |
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| `validation_status` | string | accepted |
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| `signal_clear` | string | yes (all files confirmed clear) |
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| `recording_location` | string | indoor, outdoor |
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| `background_noise_level` | string | quiet, moderate, noisy |
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| `device_type` | string | smartphone, laptop, tablet, external_mic |
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| `codec_name` | string | pcm_s16le, aac |
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## Dataset Statistics
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| CryCeleb (Ubenwa) | 6.5 hours | CC-BY-NC-ND (research only) | Speaker verification across infant identities |
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| Donate a Cry Corpus | <1 hour | Open, crowdsourced | Cry cause classification (small-scale research) |
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CryCeleb and Donate a Cry remain the leading academic resources for their respective research tasks. Our dataset complements them by providing the scale and licensing required for production-grade detection models in commercial baby monitor, sleep tracking, and smart home applications
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```python
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from datasets import load_dataset
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dataset = load_dataset("AxonData/infant-cry-detection-dataset")
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print(dataset)
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sample = dataset["train"][0]
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print(sample["audio"]) # audio array + sampling_rate
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print(sample["recording_location"]) # e.g. "indoor"
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print(sample["background_noise_level"]) # e.g. "quiet"
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print(sample["device_type"]) # e.g. "smartphone"
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```
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## Quick Start — PyTorch DataLoader
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```python
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import torch
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from datasets import load_dataset
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ds = load_dataset("AxonData/infant-cry-detection-dataset", split="train")
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def collate(batch):
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waveforms = [torch.tensor(item["audio"]["array"]) for item in batch]
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metadata = [{
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"location": item["recording_location"],
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"noise": item["background_noise_level"]
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} for item in batch]
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return waveforms, metadata
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loader = torch.utils.data.DataLoader(ds, batch_size=8, collate_fn=collate)
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```
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## Sample vs Full Version
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This HuggingFace repository contains a **sample subset** for evaluation. The full 50+ hour dataset is licensed for commercial use through Axon Labs.
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**Full version of dataset is available for commercial usage — leave a request on our website [Axonlabs](https://axonlab.ai/dataset/infant-cry-dataset/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=infant-cry&utm_content=readme) to purchase the dataset 💰**
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## What Makes This Dataset Unique
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- **Largest infant cry audio corpus
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- **Manually verified, not scraped**
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- **Authenticity-filtered**
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- **Real smartphone recordings**
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- **Backed by a biometric AI specialist** — Axon Labs builds datasets used by 21% of iBeta 2025 certified companies
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- **GDPR-compliant, ethically sourced** — explicit parental consent for all recordings
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## Two Dataset Versions Available
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- **Sample Version** — open subset for EDA, evaluation, and proof-of-concept (this repo)
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- **Full Version** — 50+ hours of audio with complete metadata, licensed for commercial training
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[Contact us](https://axonlab.ai/
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## FAQ
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**Q: How large is this dataset compared to public alternatives?**
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The full version is 50+ hours of curated infant cry audio. The most widely cited academic alternative, CryCeleb, contains 6.5 hours of cry expirations. Donate a Cry Corpus contains less than 1 hour of crowdsourced audio with documented quality issues. By volume of verified cry audio licensed for commercial training, this is the most extensive resource currently available.
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**Q: Can I use this dataset to train a production baby monitor or sleep tracking app?**
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Yes
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**Q: What metadata is provided?**
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Recording location (indoor/outdoor), background noise level (quiet/moderate/noisy), recording device type (smartphone/laptop/tablet/external microphone)
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**Q: Are there labels for cry cause (hunger, pain, discomfort)?**
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Not in this release. The dataset is designed for cry **detection** (is a cry present) and sound event detection use cases. If you need labeled cry-cause data, we can collect a custom dataset on request through our data collection service
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**Q: Is the data ethically collected?**
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Yes. All recordings were captured with explicit parental consent and documented chain of custody
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## Citation
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If you use this dataset in your research, please cite:
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```bibtex
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@misc{axonlabs2026infantcry,
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title = {Infant Cry Detection Audio Dataset},
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author = {Axon Labs},
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year = {2026},
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url = {https://axonlab.ai/dataset/infant-cry-dataset/}
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}
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```
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---
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**keywords**: infant cry dataset, baby cry dataset, infant cry detection, infant cry classification, baby cry detection, sound event detection, audio classification dataset, baby monitor dataset, smart home audio, real-world infant audio, parental tech dataset
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Visit us at [**Axonlabs**](https://axonlab.ai/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=
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---
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# Infant Cry Detection Dataset — 50+ Hours of Real Baby Cry Audio
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**50+ hours of real infant cry recordings** for training infant cry detection, cry classification, and sound event detection models. Manually verified files captured in natural domestic conditions, with per-file metadata on location, background noise, and recording device
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## Contact us and share your feedback — receive additional samples for free! 😊
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## Key Highlights
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- **50+ hours** of real-world infant cry audio
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- **Manually verified** - every recording reviewed for clear cry audibility
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- **Indoor + outdoor** capture conditions
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- **Background noise variation** - quiet, moderate, and noisy environments
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- **No synthetic audio, no augmentation, no AI-generated content**
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- Smartphone-first recordings (matches baby monitor deployment conditions)
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- **Commercial license available** - full version cleared for production use
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## Use This Dataset For
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- **Infant cry detection** - train binary or multi-class cry detectors for smart baby monitors, IoT cameras, and nursery devices
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- **Sound event detection (SED)** - cry as a target class in AudioSet-style models
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- **Sleep tracking applications** - detect cry events to estimate infant sleep quality
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- **Cry-aware smart home automation** - trigger lighting, audio response, or parent notifications
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- **Parental support apps** - distinguish cry from other infant sounds (cooing, babbling, fussing)
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- **Audio classification research** - clean, labeled training data on a focused class
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## Dataset Statistics
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| CryCeleb (Ubenwa) | 6.5 hours | CC-BY-NC-ND (research only) | Speaker verification across infant identities |
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| Donate a Cry Corpus | <1 hour | Open, crowdsourced | Cry cause classification (small-scale research) |
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CryCeleb and Donate a Cry remain the leading academic resources for their respective research tasks. Our dataset complements them by providing the scale and licensing required for production-grade detection models in commercial baby monitor, sleep tracking, and smart home applications
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**Full version of dataset is available for commercial usage — leave a request on our website [Axonlabs](https://axonlab.ai/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link) to purchase the dataset 💰**
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## What Makes This Dataset Unique
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- **Largest infant cry audio corpus** - multiple times the size of leading academic alternatives
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- **Manually verified, not scraped** - every file reviewed; suspicious files removed
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- **Authenticity-filtered** - directly addresses a documented problem in open datasets (noisy, internet-sourced contamination)
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- **Real smartphone recordings** - matches deployment conditions for baby monitor apps and smart home devices
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[Contact us](https://axonlab.ai/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link) to choose the version that fits your project.
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## FAQ
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**Q: Can I use this dataset to train a production baby monitor or sleep tracking app?**
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Yes - the full commercial version is licensed exactly for this. The sample version on HuggingFace is for evaluation, EDA, and proof-of-concept work. For production training, [request access to the full version](https://axonlab.ai/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link)
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**Q: What metadata is provided?**
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Recording location (indoor/outdoor), background noise level (quiet/moderate/noisy), recording device type (smartphone/laptop/tablet/external microphone). All files in the curated set have been confirmed as clear, original infant cry recordings
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**Q: Are there labels for cry cause (hunger, pain, discomfort)?**
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Not in this release. The dataset is designed for cry **detection** (is a cry present) and sound event detection use cases. If you need labeled cry-cause data, we can collect a custom dataset on request through our data collection service
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**Q: Is the data ethically collected?**
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Yes. All recordings were captured with explicit parental consent and documented chain of custody
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**keywords**: infant cry dataset, baby cry dataset, infant cry detection, infant cry classification, baby cry detection, sound event detection, audio classification dataset, baby monitor dataset, smart home audio, real-world infant audio, parental tech dataset
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Visit us at [**Axonlabs**](https://axonlab.ai/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link) to request a full version of the dataset for commercial usage
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