AI RESEARCH

HATS: An Open data set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metrics

arXiv CS.CL

ArXi:2604.27542v1 Announce Type: new Conventionally, Automatic Speech Recognition (ASR) systems are evaluated on their ability to correctly recognize each word contained in a speech signal. In this context, the word error rate (WER) metric is the reference for evaluating speech transcripts. Several studies have shown that this measure is too limited to correctly evaluate an ASR system, which has led to the proposal of other variants of metrics (weighted WER, BERTscore, semantic distance, etc.). However, they remain system-oriented, even when transcripts are intended for humans.