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What is Seq2Seq Model in Machine Translation about?

The document discusses the seq2seq model and its application in machine translation, highlighting the transition from statistical machine translation (SMT) to neural machine translation (NMT). It explains the encoder-decoder framework, attention mechanisms, and the advantages and disadvantages of NMT. Additionally, it covers evaluation methods like BLEU scores and the evolution of machine translation systems over time.

Author

vanbap20021599

Language

EN