Using Chat GPT to Clean Qualitative Interview Transcriptions: A Usability and Feasibility Analysis

Zachary Taylor

doi:10.29333/ajqr/14487

Zachary Taylor ¹ ^*

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AM J QUALITATIVE RES, Volume 8, Issue 2, pp. 153-160

https://doi.org/10.29333/ajqr/14487

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Abstract

One of the major inefficiencies in qualitative research is the accuracy and timeliness of transcribing audio files into analyzable text. However, researchers may now have the ability to leverage artificial intelligence to increase research efficiency through Chat GPT. As a result, this study performs feasibility and accuracy testing of Chat GPT versus human transcription to compare accuracy and timeliness. Results suggest that by using specific commands, Chat GPT can clean interview transcriptions in seconds with a <1% word error rate and near 0% syntactic error rate. Implications for research and ethics are addressed.

Keywords: Chat GPT, artificial intelligence, qualitative research, educational research, transcription

References

Agomuoh, F., & Larsen, L. (2023, September 28). What is ChatGPT? Here’s how to use the AI chatbot everyone’s talking about. DigitalTrends. https://www.digitaltrends.com/computing/how-to-use-openai-chatgpt-text-generation-chatbot/
Bock, K. (2011). “How much correction of syntactic errors are there, anyway?” Language and Linguistics Compass, 5(6), 322–335. https://doi.org/10.1111/j.1749-818X.2011.00283.x
Campbell, J.C., Hindle, A., & Amaral, J.N. (2014). Syntax errors just aren't natural: Improving error reporting with language models. In Proceedings of the 11th Working Conference on Mining Software Repositories (MSR 2014). Association for Computing Machinery, New York, NY, USA, 252–261. https://doi.org/10.1145/2597073.2597102
Crossley, S. A., Allen, D. B., & McNamara, D. S. (2011). Text readability and intuitive simplification: A comparison of readability formulas. Reading in a Foreign Language, 23(1), 84–101. https://eric.ed.gov/?id=EJ926371
Hennessy, M., Dennehy, R., Doherty, J., & O’Donoghue, K. (2022). Outsourcing transcription: Extending ethical considerations in qualitative research. Qualitative Health Research, 32(7), 1197–1204. https://doi.org/10.1177/10497323221101709
Johnson, K. (2008). Quantitative methods in linguistics. Wiley-Blackwell.
Kvale, S. (2007). Transcribing interviews: Doing interviews. SAGE Publications. https://doi.org/10.4135/9781849208963
MacLean, L. M., Meyer, M., & Estable, A. (2004). Improving accuracy of transcripts in qualitative research. Qualitative Health Research. 14(1), 113–123. https://doi.org/10.1177/1049732303259804
Microsoft. (2023). Transcribe audio files. Microsoft Office 365. https://support.microsoft.com/en-us/office/transcribe-your-recordings-7fc2efec-245e-45f0-b053-2a97531ecf57
Minkoff, S. R. B., & Raney, G. E. (2000). Letter-detection errors in the word the: Word frequency versus syntactic structure. Scientific Studies of Reading, 4(1), 55–76. https://doi.org/10.1207/S1532799XSSR0401_5
OpenAI. (2022). Introducing: Chat GPT. OpenAI. https://openai.com/blog/chatgpt
Rev. (2023). Rev automatic audio transcription. Rev. https://www.rev.com/services/auto-audio-transcription
Taylor, Z. W. (2019a). Six easy steps: Do aspiring college students understand how to apply for financial aid? Journal of Student Financial Aid, 48(3), 1–17. https://doi.org/10.55504/0884-9153.1643
Taylor, Z. W. (2019b). Writing dollars into sense: Simplifying financial aid for L2 students. Journal of Student Affairs Research and Practice, 56(4), 438–453. https://doi.org/10.1080/19496591.2019.1614937
Wang, Y.-Y., Acero, A., & Chelba, C. (2003). Is word error rate a good indicator for spoken language understanding accuracy. 2003 IEEE Workshop on Automatic Speech Recognition and Understanding, 577–582. https://doi.org/10.1109/ASRU.2003.1318504
Xiong, W., Wu, L., Alleva, F., Droppo, J., Huang, X., & Stolcke, A. (2018). The Microsoft 2017 conversational speech recognition system. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, 5934–5938. https://doi.org/10.1109/ICASSP.2018.8461870

Citation

Taylor, Z. (2024). Using Chat GPT to Clean Qualitative Interview Transcriptions: A Usability and Feasibility Analysis. American Journal of Qualitative Research, 8(2), 153-160. https://doi.org/10.29333/ajqr/14487

Taylor, Z. (2024). Using Chat GPT to Clean Qualitative Interview Transcriptions: A Usability and Feasibility Analysis. American Journal of Qualitative Research, 8(2), pp. 153-160. https://doi.org/10.29333/ajqr/14487

Taylor Z. Using Chat GPT to Clean Qualitative Interview Transcriptions: A Usability and Feasibility Analysis. AM J QUALITATIVE RES. 2024;8(2), 153-160. https://doi.org/10.29333/ajqr/14487

Taylor, Zachary. "Using Chat GPT to Clean Qualitative Interview Transcriptions: A Usability and Feasibility Analysis". American Journal of Qualitative Research 2024 8 no. 2 (2024): 153-160. https://doi.org/10.29333/ajqr/14487

Taylor, Zachary "Using Chat GPT to Clean Qualitative Interview Transcriptions: A Usability and Feasibility Analysis". American Journal of Qualitative Research, vol. 8, no. 2, 2024, pp. 153-160. https://doi.org/10.29333/ajqr/14487

Taylor Z. Using Chat GPT to Clean Qualitative Interview Transcriptions: A Usability and Feasibility Analysis. AM J QUALITATIVE RES. 2024;8(2):153-60. https://doi.org/10.29333/ajqr/14487