Introduction to the Special Section on Continuous Space and Related Methods in Natural Language Processing (Editorial)

  • Haizhou Li ,
  • Marcello Federico ,
  • Xiaodong He ,
  • Helen Meng ,
  • Isabel Trancoso

IEEE/ACM Transactions on Audio, Speech, and Language Processing |

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Natural Language Processing (NLP) aims to analyze, understand, and generate languages that humans use naturally. Significant progress in NLP has been achieved in recent years, addressing important and practical real-world problems, and enabling mass deployment of large-scale systems. New machine learning paradigms such as deep learning and continuous space methods have contributed to inferring language patterns from increasingly large real-world data and to making predictions about new data more accurate.

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