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Heterogeneous recurrent neural networks for natural language model

  • Masayuki Tsuji
  • Teijiro IsokawaEmail author
  • Takayuki Yumoto
  • Nobuyuki Matsui
  • Naotake Kamiura
Original Article
  • 8 Downloads

Abstract

Neural networks for language model are proposed and their performances are explored. The proposed network consists of two recurrent networks of which structures are different to each other. Both networks accept words as their inputs, translate their distributed representation, and produce the probabilities of words to occur from their sequence of input words. Performances for the proposed network are investigated through constructions for language models, as compared with a single recurrent neural and a long short-term memory network.

Keywords

Recurrent neural network Neural probabilistic language model Heterogeneous network 

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Copyright information

© ISAROB 2018

Authors and Affiliations

  • Masayuki Tsuji
    • 1
    • 2
  • Teijiro Isokawa
    • 1
    Email author
  • Takayuki Yumoto
    • 1
  • Nobuyuki Matsui
    • 1
  • Naotake Kamiura
    • 1
  1. 1.Graduate School of EngineeringUniversity of HyogoHimejiJapan
  2. 2.Cadence Design SystemsYokohamaJapan

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