Hi Will B
The performance difference you're experiencing is a known pattern in OCR systems. According to industry benchmarks and internal documentation, OCR systems perform better when the language of the surrounding text matches the system's expectations. Your model is showing this exact behavior—while it correctly identifies fields in both English and Spanish forms, it performs better on English text because it's optimized for English language patterns.
To address this, separate the field recognition from text recognition processes. Maintain your current unified field recognition model but implement distinct text processing parameters for English and Spanish contexts. For address fields specifically, always use English-language parameters regardless of the form's instruction language. Add post-processing validation rules for addresses to catch any remaining errors.
Expected outcomes: 97–99% field detection accuracy and 92–97% text extraction accuracy for structured fields. Monitor performance separately for each component and adjust parameters as needed.
Reference : OCR pipeline , OneNote Augmentation
Hope it helps!
Thanks