43 citations · 47 across the 5 of their papers we have counts for
3 papers · 1 filter
OpenWER: Improving Cross-Lingual ASR Evaluation and Enabling Token-Based Accuracy Metrics
Korbinian Kuhn, Gottfried Zimmermann
Advances in deep learning and end-to-end Automatic Speech Recognition (ASR) have enabled robust multilingual models, but evaluation metrics remain limited in assessing accuracy. Ef…
Measuring the Accuracy of Automatic Speech Recognition Solutions
Korbinian Kuhn, Verena Kersken, Benedikt Reuter +2
For d/Deaf and hard of hearing (DHH) people, captioning is an essential accessibility tool. Significant developments in artificial intelligence (AI) mean that Automatic Speech Reco…
Beyond Levenshtein: Leveraging Multiple Algorithms for Robust Word Error Rate Computations And Granular Error Classifications
Korbinian Kuhn, Verena Kersken, Gottfried Zimmermann
The Word Error Rate (WER) is the common measure of accuracy for Automatic Speech Recognition (ASR). Transcripts are usually pre-processed by substituting specific characters to acc…