Linguistically Informed Hindi-English Neural Machine Translation

LREC 2020 • Vikrant Goyal • Pruthwik Mishra • Dipti Misra Sharma

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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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

METHOD

TYPE

Residual Connection