Consensus automatic speech recognition (CASR) in the California Cognitive Assessment Battery (CCAB)

Recent reports have investigated the use of automatic speech recognition (ASR) to analyze and score verbal responses in cognitive tests. ASR scoring is objective, permits the efficient computerized administration of verbal tests, and generates timestamps that enable the detailed temporal analysis of responses. However, ASR transcription accuracy varies by engine, task, and participant, and ASR can incorrectly score responses from participants with atypical speech patterns. Here we describe the speech‐transcription pipeline of the California Cognitive Assessment Battery (CCAB), which incorporates consensus ASR (CASR) to produce more accurate transcripts than possible with any single ASR engine. We also developed a Transcript Review Tool (TRT) which facilitates the manual correction of mis‐transcribed words in problem subjects.