Linguistically Informed Hindi-English Neural Machine Translation

Hindi-English Machine Translation is a challenging problem, owing to multiple factors including the morphological complexity and relatively free word order of Hindi, in addition to the lack of sufficient parallel training data. Neural Machine Translation (NMT) is a rapidly advancing MT paradigm and has shown promising results for many language pairs, especially in large training data scenarios... (read more)

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Methods used in the Paper


METHOD TYPE
Residual Connection
Skip Connections
Label Smoothing
Regularization
Multi-Head Attention
Attention Modules
Adam
Stochastic Optimization
ReLU
Activation Functions
Dropout
Regularization
BPE
Subword Segmentation
Dense Connections
Feedforward Networks
Layer Normalization
Normalization
Softmax
Output Functions
Scaled Dot-Product Attention
Attention Mechanisms
Transformer
Transformers