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README.md

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+---
+license: apache-2.0
+tags:
+  - speaker-embedding
+  - speaker-verification
+  - speechbrain
+  - ecapa-tdnn
+  - audio
+library_name: speechbrain
+pipeline_tag: audio-classification
+---
+
+# Speaker Embedding Endpoint
+
+Custom HuggingFace Inference Endpoint for extracting speaker embeddings using SpeechBrain's ECAPA-TDNN model.
+
+## Model
+
+This endpoint uses [speechbrain/spkrec-ecapa-voxceleb](https://huggingface.co/speechbrain/spkrec-ecapa-voxceleb) model which achieves:
+- **0.80% EER** on VoxCeleb1 test set
+- **192-dimensional** speaker embeddings
+
+## Usage
+
+### API Request
+
+```bash
+curl -X POST \
+  https://your-endpoint-url.endpoints.huggingface.cloud \
+  -H "Authorization: Bearer YOUR_HF_TOKEN" \
+  -H "Content-Type: audio/wav" \
+  --data-binary "@audio.wav"
+```
+
+### Response
+
+```json
+{
+  "embedding": [0.123, -0.456, ...],
+  "dimension": 192,
+  "model": "speechbrain/spkrec-ecapa-voxceleb"
+}
+```
+
+## Speaker Verification
+
+To verify if two audio files are from the same speaker:
+
+1. Extract embeddings from both audio files
+2. Calculate cosine similarity between embeddings
+3. If similarity > 0.6 (threshold), same speaker
+
+```python
+from scipy.spatial.distance import cosine
+
+similarity = 1 - cosine(embedding1, embedding2)
+is_same_speaker = similarity > 0.6
+```
+
+## Project
+
+Part of **Deep Truth** - AI Deepfake Voice Detection & Speaker Verification Service
+
+- GitHub: https://github.com/yonghwan1106/deep-truth
+- Demo: https://deep-truth.vercel.app