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Related Questions
- What are some common pitfalls to avoid when training machine translation models to minimize cultural bias?
- How can linguists and cultural experts be involved in the development of machine translation systems to ensure cultural sensitivity?
- What are some strategies for evaluating the cultural bias of machine translation outputs, and how can they be used to improve model performance?
- Can you explain the role of data curation in reducing cultural bias in machine translation, and what types of data are most effective for this purpose?
- How can machine translation systems be designed to accommodate diverse cultural norms and conventions, such as honorifics and idiomatic expressions?
- What are some best practices for testing and validating machine translation outputs for cultural bias, and how can they be integrated into the development pipeline?
- Can you discuss the importance of considering cultural context in machine translation, and how this can be achieved through techniques such as contextualized embeddings and multimodal input?
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