Deep Text Corrector uses TensorFlow to train sequence-to-sequence models that are capable of automatically correcting small grammatical errors in conversational written English (e.g. SMS messages). It does this by taking English text samples that are known to be mostly grammatically correct and randomly introducing a handful of small grammatical errors (e.g. removing articles) to each sentence to produce input-output pairs (where the output is the original sample), which are then used to train a sequence-to-sequence model.
文本糾錯使用TensorFlow訓練序列到序列模型,該模型能夠自動糾正會話書面英語中的小語法錯誤。 為此,它采用已知大部分語法正確的英語文本樣本,并在每個句子中隨機引入少量小語法錯誤(例如,刪除文章),以產(chǎn)生輸入輸出對(其中輸出是原始樣本), 然后用于訓練序列到序列模型。