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Related Questions
- What are the common preprocessing techniques used to filter out noisy or irrelevant data in back-translation?
- How can data cleaning and normalization be applied to improve the quality of the original data?
- What are the benefits of removing stop words and punctuation from the original data in back-translation?
- Can you explain the concept of stemming and lemmatization, and how they can be used to preprocess the original data?
- What is the role of tokenization in back-translation, and how can it be used to filter out irrelevant data?
- How can named entity recognition (NER) be used to identify and filter out irrelevant entities in the original data?
- What are the best practices for handling out-of-vocabulary (OOV) words in the original data, and how can they be addressed in back-translation?
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