Advances in natural language processing.

Journal: Science (New York, N.Y.)
Published Date:

Abstract

Natural language processing employs computational techniques for the purpose of learning, understanding, and producing human language content. Early computational approaches to language research focused on automating the analysis of the linguistic structure of language and developing basic technologies such as machine translation, speech recognition, and speech synthesis. Today's researchers refine and make use of such tools in real-world applications, creating spoken dialogue systems and speech-to-speech translation engines, mining social media for information about health or finance, and identifying sentiment and emotion toward products and services. We describe successes and challenges in this rapidly advancing area.

Authors

  • Julia Hirschberg
    Department of Computer Science, Columbia University, New York, NY 10027, USA. julia@cs.columbia.edu.
  • Christopher D Manning
    Department of Linguistics, Stanford University, Stanford, CA 94305-2150, USA. Department of Computer Science, Stanford University, Stanford, CA 94305-9020, USA.