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Explore the comprehensive field of multilingual natural language processing through this 17-hour 41-minute course series from Carnegie Mellon University. Begin with foundational concepts including sequence labeling, typology, and morphological analysis before progressing to advanced topics in machine translation, speech processing, and cross-lingual transfer learning. Master translation models and data-driven strategies for neural machine translation, then delve into specialized areas such as unsupervised machine translation, code switching, and multilingual question answering. Examine speech technologies including automatic speech recognition, text-to-speech systems, and multilingual ASR approaches. Study syntactic parsing across languages, active learning methodologies, and real-world applications through the LORELEI project. Learn evaluation techniques for machine translation systems and explore the critical field of endangered language documentation. Gain insights into language contact, change, and the development of pidgins and creoles, while understanding how multilingual training and transfer learning can be applied across diverse linguistic contexts.
