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.
文本纠错使用TensorFlow训练序列到序列模型,该模型能够自动纠正会话书面英语中的小语法错误。 为此,它采用已知大部分语法正确的英语文本样本,并在每个句子中随机引入少量小语法错误(例如,删除文章),以产生输入输出对(其中输出是原始样本), 然后用于训练序列到序列模型。