Multilingual Hybrid Processing Technology Program
SmolDocling provides the following solutions to the problem of language mixing in internationalized business documents:
- Language Detection Optimization1) Built-in 37 language classifiers 2) Supports automatic language switching at paragraph level 3) Can be forced to specify language combinations (e.g.
langs=["en","ja"]) - mixed coding process1) Adopts UTF-8 superset encoding 2) Optimized for CJK characters (CJK) 3) Automatically adjusts text flow when dealing with RTL languages such as Arabic.
- Typical issues addressed: 1) Pinyin-mixed Chinese: Enabled
pinyin2hanziConversion 2) Bilingual documentation: uselayout="parallel"Parameters maintain correspondence 3) Special symbols: maintain customized mapping table
Implementation Suggestions: 1) Prioritize columnar documents with clear language boundaries 2) Train adaptation models incrementally for low-resource languages 3) Retain the original text position information for easy proofreading when outputting.
This answer comes from the articleSmolDocling: a visual language model for efficient document processing in a small volumeThe
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