| This model is a Sound Event Detection (SED) system designed to detect and extract specific audio events from long-form recordings. It is built on the PANNs (Pretrained Audio Neural Networks) architecture, specifically utilizing the CNN14 backbone with a Multiple Instance Learning (MIL) head for weak-label training and frame-level inference. |
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| ## Model Details |
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| - **Architecture:** CNN14 (PANNs) + MIL Head |
| - **Task:** Sound Event Detection (SED) / Audio Classification |
| - **Input Sampling Rate:** 32,000 Hz |
| - **Primary Target:** Specific sound event detection (e.g., sniffing, breathing, or vocalizations depending on the finetuning dataset). |
| - **Time Resolution:** ~10ms - 160ms depending on the hop size and pooling configuration. |
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| ## Disclaimer |
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| This repository contains the **model weights only**. It is not a standalone executable and requires a compatible PANNs-based inference script to function. |
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| This model is part of a project called AccuSlice-SED that hasn't rolled out yet. I wanted to upload the weight to my private repository, but I was told "You've reached private storage quota. Upload it to public!" so I'm doing this reluctantly. :/ |
