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Comparing Recurrent and Convolutional Architectures for English-Hindi Neural Machine Translation

2017-11-01 · WS 2017 11 · S. Singh, hya, Ritesh Panjwani, Anoop Kunchukuttan, Pushpak Bhattacharyya

In this paper, we empirically compare the two encoder-decoder neural machine translation architectures: convolutional sequence to sequence model (ConvS2S) and recurrent sequence to sequence model (RNNS2S) for English-Hindi language pair as part of IIT Bombay{'}s submission to WAT2017 shared task. We report the results for both English-Hindi and Hindi-English direction of language pair.

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DecoderImage CaptioningLanguage ModelingLanguage ModellingMachine TranslationQuestion AnsweringTranslationWord Embeddings

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