SEQUENCE TO SEQUENCE LEARNING USING WORD AND CHARACTER REPRESENTATION AND NAMED ENTITY INFORMATION FOR MACHINE TRANSLATION
Sequence to sequence learning tries to directly model a sequence of words from the source sentence into a sequence of words of target sentence. Most of sequence to sequence learning uses RNN model with an encoder – decoder framework. Neural Machine Translation (NMT) is one application of sequence...
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| 格式: | Theses |
| 語言: | Indonesia |
| 在線閱讀: | https://digilib.itb.ac.id/gdl/view/28459 |
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| 機構: | Institut Teknologi Bandung |
| 語言: | Indonesia |