NLP for Multilingual Applications: Challenges and Techniques
NLP for Multilingual Applications: Challenges and Techniques NLP for multilingual applications aims to understand and generate text in many languages. Users expect smooth experiences in their own language, whether they chat with a bot, search, or read recommendations. The task goes beyond simple translation. It includes language detection, tokenization, sentiment, and topic understanding across scripts and dialects. A practical approach combines powerful multilingual models with careful data, evaluation, and bias checks. The result should be accurate, respectful, and useful in real world scenarios. ...