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Text style transfer using reinforcement learning

机译:基于强化学习的文本风格迁移

摘要

A computer-implemented method is provided for transferring a target text style using Reinforcement Learning (RL). The method includes pre-determining, by a Long Short-Term Memory (LSTM) Neural Network (NN), the target text style of a target-style natural language sentence. The method further includes transforming, by a hardware processor using the LSTM NN, a source-style natural language sentence into the target-style natural language sentence that maintains the target text style of the target-style natural language sentence. The method also includes calculating an accuracy rating of a transformation of the source-style natural language sentence into the target-style natural language sentence based upon rewards relating to at least the target text style of the source-style natural language sentence.
机译:提供了一种使用强化学习(RL)传递目标文本样式的计算机实现方法。该方法包括通过长短时记忆(LSTM)神经网络(NN)预先确定目标风格自然语言句子的目标文本风格。该方法还包括通过使用LSTM NN的硬件处理器将源样式自然语言句子转换为目标样式自然语言句子,该目标样式自然语言句子保持目标样式自然语言句子的目标文本样式。该方法还包括基于至少与源风格自然语言句子的目标文本风格相关的奖励,计算源风格自然语言句子到目标风格自然语言句子的转换的准确度等级。

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