4 papers
Evaluating ASR Confidence Scores for Automated Error Detection in User-Assisted Correction Interfaces
Korbinian Kuhn, Verena Kersken, Gottfried Zimmermann
Despite advances in Automatic Speech Recognition (ASR), transcription errors persist and require manual correction. Confidence scores, which indicate the certainty of ASR results,…
Communication Access Real-Time Translation Through Collaborative Correction of Automatic Speech Recognition
Korbinian Kuhn, Verena Kersken, Gottfried Zimmermann
Communication access real-time translation (CART) is an essential accessibility service for d/Deaf and hard of hearing (DHH) individuals, but the cost and scarcity of trained perso…
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…