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--- |
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language: |
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- ar |
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tags: |
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- text-classification |
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- eou |
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- end-of-utterance |
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- turn-detection |
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- arabic |
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- saudi-dialect |
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- marbert |
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base_model: UBC-NLP/MARBERT |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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--- |
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# MARBERT Arabic End-of-Utterance Detection |
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Fine-tuned MARBERT model for Arabic End-of-Utterance (EOU) detection in real-time voice agents. |
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## Model Description |
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- **Base Model:** UBC-NLP/MARBERT (163M parameters) |
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- **Task:** Binary sequence classification (complete vs incomplete utterance) |
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- **Language:** Arabic (emphasis on Saudi/Gulf dialect) |
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- **Training Data:** 125K samples from SADA22 dataset |
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- **Inference Speed:** ~30ms average latency on CPU |
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## Performance |
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| Metric | Score | |
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|--------|-------| |
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| **F1 Score** | 0.8174 | |
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| **Accuracy** | 0.7995 | |
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| **Precision** | 0.7506 | |
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| **Recall** | 0.8971 | |
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| **AUC-ROC** | 0.8249 | |
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**Test Set:** 31,289 samples (50% complete, 50% incomplete) |
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## Usage |
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```python |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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import torch |
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model = AutoModelForSequenceClassification.from_pretrained("azeddinShr/marbert-arabic-eou") |
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tokenizer = AutoTokenizer.from_pretrained("azeddinShr/marbert-arabic-eou") |
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def predict_eou(text): |
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inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=128) |
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with torch.no_grad(): |
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outputs = model(**inputs) |
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probs = torch.softmax(outputs.logits, dim=-1) |
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eou_prob = probs[0][1].item() |
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return eou_prob |
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# Example |
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text = "شكرا جزيلا على المساعدة" |
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prob = predict_eou(text) |
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is_complete = prob > 0.5 |
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print(f"EOU Probability: {prob:.3f} - {'Complete' if is_complete else 'Incomplete'}") |
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``` |
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## Training Details |
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- **Epochs:** 6 |
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- **Batch Size:** 16 (train), 32 (eval) |
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- **Learning Rate:** 2e-5 |
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- **Optimizer:** AdamW |
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- **Max Length:** 128 tokens |
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- **Training Time:** ~2 minutes (GPU) |
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## Use Cases |
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- Real-time Arabic voice agents |
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- Turn-taking detection in conversations |
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- Streaming speech-to-text applications |
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- Voice assistant interrupt handling |
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## Limitations |
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- Best performance on Saudi/Gulf Arabic dialects |
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- Requires Arabic text input (not audio) |
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## Citation |
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```bibtex |
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@model{marbert-arabic-eou, |
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author = {azeddinShr}, |
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title = {MARBERT Arabic End-of-Utterance Detection}, |
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year = {2025}, |
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publisher = {HuggingFace}, |
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url = {https://huggingface.co/azeddinShr/marbert-arabic-eou} |
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} |
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``` |
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## Dataset |
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Training dataset: [azeddinShr/arabic-eou-sada22](https://huggingface.co/datasets/azeddinShr/arabic-eou-sada22) |
