Equalizing Gender Biases in Neural Machine Translation with Word Embeddings Techniques

Understand

Neural machine translation has significantly pushed forward the quality of the field.

• However, there are remaining big issues with the output translations and one of them is fairness.
• Neural models are trained on large text corpora which contain biases and stereotypes.
• As a consequence, models inherit these social biases.