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 |

Publication

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.