Language Identification

Language identification (LID) focuses on automatically determining the language of a given text or speech input, a crucial preprocessing step for many natural language processing and speech processing applications. Current research emphasizes improving LID accuracy for low-resource languages, handling code-switching (mixing of languages within a single utterance), and addressing challenges posed by noisy or unconventional data, often employing transformer-based models, Gaussian Mixture Models, and Connectionist Temporal Classification (CTC) approaches. Advances in LID are vital for enhancing multilingual natural language understanding, improving access to information for speakers of under-resourced languages, and enabling more robust and inclusive applications in fields like machine translation and speech recognition.