---
tags:
- speechbrain
- ecapa-tdnn
- speaker-verification
- speaker-recognition
- vietnamese
---

# Fine-tuned ECAPA-TDNN for Vietnamese Speaker Verification

This model is a fine-tuned ECAPA-TDNN speaker embedding model based on
`speechbrain/spkrec-ecapa-voxceleb`.

## Training

- Fine-tuning dataset: Vietnam-Celeb
- Selected checkpoint: Epoch 10
- Embedding dimension: 192
- Sample rate: 16 kHz

## Verification Pipeline

Audio
→ CRDNN VAD
→ ECAPA-TDNN embedding
→ L2 normalization
→ 5-recording enrollment
→ mean speaker centroid
→ cosine similarity
→ threshold decision

Final DEV-calibrated threshold:

`0.1566`

## Speaker-disjoint Evaluation

All-impostor evaluation protocol:

| Model | DEV EER | TEST EER | TEST FAR | TEST FRR |
|---|---:|---:|---:|---:|
| Pretrained ECAPA | 13.30% | 11.91% | 9.46% | 13.47% |
| Fine-tuned Epoch 10 | 9.98% | 8.42% | 9.00% | 7.88% |

TEST evaluation:

- 50 unseen speakers
- 5 enrollment recordings per speaker
- 698 genuine trials
- 34,202 impostor trials
- No speaker overlap between train/DEV/TEST

The TEST threshold was not tuned on TEST.
The final threshold was calibrated only on DEV.

## Base Model

SpeechBrain:
`speechbrain/spkrec-ecapa-voxceleb`

## Limitations

This model is intended for an academic prototype of a speaker-verification
system. The reported FAR is not low enough to claim production-grade
security.

Performance may vary with microphone quality, background noise, language,
recording duration, and speaker characteristics.

## Files

- `ecapa_vietnamceleb_epoch10.pt`: fine-tuned ECAPA embedding checkpoint
- `config.json`: deployment configuration and verification threshold
- `all_impostor_metrics.json`: detailed evaluation metrics
- `pretrained_vs_finetuned.csv`: baseline comparison