Text Style Transfoer

Text Style Transfer is an important task in natural language processing, aiming to control specific attributes of the generated text, such as sentiment and tone. This task can be achieved through supervised methods using parallel data and unsupervised methods using non-parallel data. The former employs neural sequence models with an encoder-decoder architecture, while the latter adopts techniques like disentanglement, prototype editing, and pseudo-parallel corpus construction. Text Style Transfer has significant application value in areas such as text generation and sentiment analysis, and the Yelp Review Dataset is commonly used as a benchmark dataset, with metrics like sentiment accuracy, BLEU, and PPL being used for evaluation.