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