NLP & Speech
Columbia researchers are using natural language processing tools to extract text from news reports, feeds, and social media to automatically summarize key points.
“Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms” laid the foundation for how to use machine learning methods across a range of NLP tasks.
Using AI techniques, Kathleen McKeown and Julia Hirschberg are creating an automated, universal sentiment detection system for new languages, including low-resource languages where translators are few.
About
Natural Language Processing and Spoken Language Processing involves computational approaches to the analysis and generation of text and speech. At Columbia these include text and speech summarization, question answering, machine translation, syntax and parsing, language generation, spoken dialogue systems, semantic representation and analysis, and the study of emotional and deceptive speech, in English, Arabic, and Mandarin, inter alia.
Spoken Language Processing Group 
Natural Language Processing Group 
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