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New Metric For Indic ASR Evaluation Developed

Modernity/arxiv India 1h Impact 5
Researchers have developed SN-WER, a Script-Normalized Word Error Rate metric for multi-script Indic Automatic Speech Recognition evaluation. This metric aims to better assess ASR performance when references and hypotheses encode different scripts.

Topics

ASR speech recognition metric

Developing

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Sources · 7 independent

Modernity/arxiv

“SN-WER: Script-Normalized WER for Multi-Script Indic ASR Evaluation. Authors: Priyaranjan Pattnayak 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 ...”

Modernity/arxiv

“the dominant metric for automatic speech recognition (ASR), but it can overestimate errors when references and hypotheses encode the ... Pluralistic Leaderboards. Authors: Nika Haghtalab, Ariel D. Procaccia, Han Shao, Serena Lutong Wang, Kunhe Yang Abstract: Recent leaderboard-based evaluations of large language models aggregate user feedback by fitting a Brad...”

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