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---
language: en
tags:
- audio-classification
- causal-representation
- infant-cry-detection
license: mit
datasets:
- custom-audio-dataset
metrics:
- event-based-f1
- iou
- accuracy
---
# Infant Cry Detection Using Causal Temporal Representation
This model detects infant cries using a novel **causal temporal representation** framework. By integrating causal reasoning into the data-generating process (DGP), the model aims to enhance the interpretability and reliability of cry detection systems.
## Features
- **Causal Data Generating Process**: Incorporates mathematical causal assumptions to define the relationship between audio features and annotations.
- **Supervised Models**: Includes pre-trained state-of-the-art models:
- Bidirectional LSTM
- Transformer
- MobileNet V2
- **Event-Based Metrics**: Tailored for time-sensitive detection tasks:
- Event-based F1-score
- Intersection over Union (IOU)
- **Interactive Example**: Jupyter Notebook with step-by-step usage demonstrations.
---
## How to Use
You can load the model directly from Hugging Face:
```python
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