SN-WER: Script-Normalized WER for Multi-Script Indic ASR Evaluation 事件

SN-WER: Script-Normalized WER for Multi-Script Indic ASR Evaluation arXiv:2606.02548v1 Announce Type: new Abstract: Word Error Rate (WER) is the dominant metric for automatic speech recognition (ASR), but it can overestimate errors when references and hypotheses encode the same words in different scripts. This issue is common in multilingual settings where ASR models may emit romanized text. We propose Script-Normalized WER (SN-WER), a training-free, evaluation-only scoring method that translit