arabic-eou-model

Arabic End-of-Utterance (EOU) Detection Model

Model Description

Fine-tuned model for Arabic End-of-Utterance detection, optimized for Saudi dialect conversations. Designed for real-time integration with LiveKit voice agents.

Performance Metrics (Step 2400)

Intended Use

• Real-time voice agent turn detection
• Arabic conversational AI systems
• Saudi dialect speech processing

Training Details

• Base Model: [specify your base model]
• Training Steps: 2400
• Validation Loss: 0.462
• Training Date: December 2024

Usage

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("{username}/{repo_name}")
tokenizer = AutoTokenizer.from_pretrained("{username}/{repo_name}")

# Example inference
text = "نعم، أنا أفهم ما تقصد"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
eou_probability = torch.softmax(outputs.logits, dim=-1)[0][1].item()

Limitations

• Optimized for Saudi dialect
• May require threshold tuning for specific use cases
• Designed for conversational contexts

Citation

@misc{arabic-eou-2024,
  author = {Your Name},
  title = {Arabic EOU Detection Model},
  year = {2024},
  publisher = {HuggingFace},
  url = {https://huggingface.co/{username}/{repo_name}}
}