Evaluating Web-Based Automatic Transcription for Alzheimer Speech Data: Transcript Comparison and Machine Learning Analysis.
Thomas SoroskiThiago da Cunha VascoSally Newton-MasonSaffrin GranbyCaitlin LewisAnuj HarisinghaniMatteo RizzoCristina ConatiGabriel MurrayGiuseppe CareniniThalia Shoshana FieldHyeju JangPublished in: JMIR aging (2022)
We found that automatically transcribed speech data could be used to distinguish patients with a diagnosis of AD, MCI, or SMC from controls. We recommend a human verification step to improve the performance of automatic transcripts, especially for spontaneous tasks. Moreover, human verification can focus on correcting errors and adding punctuation to transcripts. However, manual addition of pauses is not needed, which can simplify the human verification step to more efficiently process large volumes of speech data.