Vietnamese Accent Marker XLM-RoBERTa

What is vietnamese-accent-marker-xlm-roberta?

This is a specialized transformer model designed to automatically insert accent marks (diacritics) into Vietnamese text. Built upon the XLM-RoBERTa architecture, it achieves an impressive 97% accuracy in predicting correct diacritical marks, outperforming traditional HMM-based approaches. The model treats accent insertion as a token classification problem, where each input token is assigned a specific tag that transforms it into its properly accented form.

Implementation Details

The model implements a sophisticated token classification approach using XLM-RoBERTa as its foundation. It processes input text by tokenizing words and predicting appropriate accent tags from a predefined set of 528 possible transformations. The system operates in three main steps: tokenization, prediction of accent tags, and accent application to generate the final output.

• Utilizes XLM-RoBERTa's powerful contextual understanding for accurate accent prediction
• Handles a maximum of 512 tokens per input sequence
• Implements a custom tag-based transformation system for accent application
• Supports both fully unaccented and partially accented input text

Core Capabilities

• Accurate diacritical mark prediction for Vietnamese text
• Support for mixed accented/unaccented input processing
• Batch processing capability for efficient text transformation
• Context-aware accent prediction using transformer architecture
• Production-ready implementation with PyTorch backend