OpenWER introduces an open-source framework that improves Word Error Rate robustness through language-specific normalization and compound word detection. It enables token-based Levenshtein alignment, supporting granular accuracy metrics and metadata embedding. Analysis of 52 languages shows up to 25% absolute WER reductions, advancing fair cross-lingual ASR evaluation.