Selected article for: "long short term memory and lstm model long short term memory"
Author: Slim, Amel; Melouah, Ahlem; Faghihi, Yousef; Sahib, Khouloud
Title: Algerian Dialect Translation Applied on COVID-19 Social Media Comments
  • Cord-id: h381gh0c
  • Document date: 2020_10_30
    • ID: h381gh0c
    Snippet: This work is part of a study on the propagation of misinformation about COVID-19 and its impact on Algerian society. It studies the problem of Algerian dialect translation applied to COVID-19 social media communications. The proposed system begins by filtering messages to identify comments that talk about COVID-19. Then, COVID-19 texts are translated from the Algerian dialect to formal standard Arabic. The filtering process is based on the long short-term memory (LSTM) model. The translation pro
    Document: This work is part of a study on the propagation of misinformation about COVID-19 and its impact on Algerian society. It studies the problem of Algerian dialect translation applied to COVID-19 social media communications. The proposed system begins by filtering messages to identify comments that talk about COVID-19. Then, COVID-19 texts are translated from the Algerian dialect to formal standard Arabic. The filtering process is based on the long short-term memory (LSTM) model. The translation process is based on the embedding-GRU model. Experimental results give precision rates of about 99.98% in the filtering process and about 97.56% in the translation process. The achieved BLUE score is 22.10.

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