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Explore the renaissance of Natural Language Processing (NLP) in cognitive computing through this 58-minute lecture by Salim Roukos from IBM T.J Watson Research Center. Delve into the unprecedented volume, variety, velocity, and veracity of electronically available multi-modal data, and discover how it's driving increased interest in cognitive computing. Learn about IBM's novel statistical models for NLP, including statistical parsing, question-answering systems, and machine translation. Examine the significant progress in statistical machine translation quality, focusing on techniques like source language analysis, cross-system adaptation, and improved data modeling for informal communications. Gain insights into methods for enhancing machine translation value for human translators, particularly in challenging language pairs like English to Japanese. Understand the impact of machine translation on human translator productivity and explore the future of human-machine interactions in NLP.
