AI RESEARCH
Utterance-Level Methods for Identifying Reliable ASR-Output for Child Speech
arXiv CS.CL
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ArXi:2604.19801v1 Announce Type: cross Automatic Speech Recognition (ASR) is increasingly used in applications involving child speech, such as language learning and literacy acquisition. However, the effectiveness of such applications is limited by high ASR error rates. The negative effects can be mitigated by identifying in advance which ASR-outputs are reliable. This work aims to develop two novel approaches for selecting reliable ASR-output at the utterance level, one for selecting reliable read speech and one for dialogue speech material.