Language Detection

Language detection, the automated identification of a spoken or written text's language, aims to improve cross-lingual communication and analysis of multilingual data. Current research focuses on enhancing accuracy and robustness across diverse scenarios, including low-resource languages, transliterated text, and the presence of noise or code-switching, employing techniques like transformer-based models (e.g., BERT), and probabilistic methods such as PLDA. These advancements are crucial for applications ranging from social media monitoring and content moderation to improving the performance of downstream natural language processing tasks in multilingual settings.