Since the less fluent sentences are generated by the error generation seq2seq model trained with error-corrected data, they usually do not change the original sentence's meaning; thus, they can be paired with their correct sentences, establishing fluency boost sentence pairs that can be used as training instances for error correction models, as Figure 3(a) shows.
we first train a seq2seq error generation model Θ gen with S * which is identical to S * except that the source sentence and the target sentence are interchanged.