NLP Multi-Language Processing — Cross-Lingual Text Analysis

I will build a multilingual NLP system for your cross-lingual text processing needs — covering language detection, multilingual classification or extraction using XLM-RoBERTa or mBERT, translation-augmented processing for languages without sufficient training data, and a unified output schema aggregating results across all languages consistently. Multinational businesses processing customer feedback, support tickets, or documents in multiple languages cannot afford separate monolingual models for each language they support — a properly designed cross-lingual system using multilingual transformer models handles dozens of languages from a single model with competitive performance across all of them.

The system covers language detection, multilingual classification or NER using XLM-RoBERTa, translation-augmented processing for low-resource languages, unified output schema across languages, per-language evaluation metrics, and a deployment API handling mixed-language input batches.