Patents by Inventor Muyun YANG

Muyun YANG has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Parameter adjustment method used for statistical machine translation
    Patent number: 9460087
    Abstract: The present invention relates to a parameter adjustment method. The parameter adjustment method used for statistical machine translation comprises: step 1: using a monolingual corpus to construct a language model required for translation; step 2: using a bilingual parallel corpus to construct a translation model; and step 3: using a target function to adjust a parameter. The method can solve problems in prior art that the parameter is easily over-fit or falls into a local optimum during a parameter adjustment process, and the method is easy to implement and can combine a larger number of features. In addition, the target function is convex; therefore, global optimum can be achieved in a training process.
    Type: Grant
    Filed: December 2, 2013
    Date of Patent: October 4, 2016
    Inventors: Hailong Cao, Wenwen Zhang, Lemao Liu, Tiejun Zhao, Muyun Yang, Dequan Zheng, Conghui Zhu, Bing Xu
  • PARAMETER ADJUSTMENT METHOD USED FOR STATISTICAL MACHINE TRANSLATION
    Publication number: 20160004691
    Abstract: The present invention relates to a parameter adjustment method. The parameter adjustment method used for statistical machine translation comprises: step 1: using a monolingual corpus to construct a language model required for translation; step 2: using a bilingual parallel corpus to construct a translation model; and step 3: using a target function to adjust a parameter. The method can solve problems in prior art that the parameter is easily over-fit or falls into a local optimum during a parameter adjustment process, and the method is easy to implement and can combine a larger number of features. In addition, the target function is convex; therefore, global optimum can be achieved in a training process.
    Type: Application
    Filed: December 2, 2013
    Publication date: January 7, 2016
    Inventors: Hailong CAO, Wenwen ZHANG, Lemao LIU, Tiejun ZHAO, Muyun YANG, Dequan ZHENG, Conghui ZHU, Bing XU