Expedited transcription methods (Fox et al., 2021)
journal contributionposted on 18.08.2021, 23:54 authored by Carly B. Fox, Megan Israelsen-Augenstein, Sharad Jones, Sandra Laing Gillam
Purpose: This study examined the accuracy and potential clinical utility of two expedited transcription methods for narrative language samples elicited from school-age children (7;5–11;10 [years;months]) with developmental language disorder. Transcription methods included real-time transcription produced by speech-language pathologists (SLPs) and trained transcribers (TTs) as well as Google Cloud Speech automatic speech recognition.
Method: The accuracy of each transcription method was evaluated against a gold-standard reference corpus. Clinical utility was examined by determining the reliability of scores calculated from the transcripts produced by each method on several language sample analysis (LSA) measures. Participants included seven certified SLPs and seven TTs. Each participant was asked to produce a set of six transcripts in real time, out of a total 42 language samples. The same 42 samples were transcribed using Google Cloud Speech. Transcription accuracy was evaluated through word error rate. Reliability of LSA scores was determined using correlation analysis.
Results: Results indicated that Google Cloud Speech was significantly more accurate than real-time transcription in transcribing narrative samples and was not impacted by speech rate of the narrator. In contrast, SLP and TT transcription accuracy decreased as a function of increasing speech rate. LSA metrics generated from Google Cloud Speech transcripts were also more reliably calculated.
Conclusions: Automatic speech recognition showed greater accuracy and clinical utility as an expedited transcription method than real-time transcription. Though there is room for improvement in the accuracy of speech recognition for the purpose of clinical transcription, it produced highly reliable scores on several commonly used LSA metrics.
Supplemental Material S1. Example prepared transcripts from each source.
Supplemental Material S2. Preparation process.
Supplemental Material S3. Descriptives for SALT indices by transcription method.
Fox, C. B., Israelsen-Augenstein, M., Jones, S., & Gillam, S. L. (2021). An evaluation of expedited transcription methods for school-age children’s narrative language: Automatic speech recognition and real-time transcription. Journal of Speech, Language, and Hearing Research. Advance online publication. https://doi.org/10.1044/2021_JSLHR-21-00096
This research was funded through the Graduate Research & Opportunities Grant awarded by Utah State University.
Read the peer-reviewed publication
languagechildrentranscriptiontranscribeschool-agenarrativemethodsexpeditedautomaticspeechrecognitionreal-timeaccuracyclinicalutilitylanguage sampledevelopmental language disorderDLDspeech-language pathologistSLPGoogle Cloud Speechreliabilitylanguage sample analysisLSAtranscripterror ratespeech rateLanguageLinguistic Processes (incl. Speech Production and Comprehension)Laboratory Phonetics and Speech Science