Is Automatic Transcription a Good Practice For Qualitative Research Methodology?

Automatic transcription refers to the use of artificial intelligence (AI) technology to convert spoken language into written text. It facilitates the transformation of audio-recorded interviews, focused group discussions, lectures, speeches, and other spoken content into a text format that can be easily analyzed and referenced. For researchers, it is a tool that can considerably reduce the period and effort required to transcribe large volumes of audio data.

Automatic transcription is critical in qualitative research methodology, particularly in data analysis. Qualitative research often involves the collection of vast amounts of verbal data through interviews or focused groups and the detailed analysis of these data to uncover patterns, themes, and insights. Historically, transcription of these data has been a time-consuming manual process, often requiring hours of listening and typing for each hour of recorded data.

With the emergence of automatic transcription software, analysts have been able to cut down on this period drastically. This technology uses sophisticated algorithms to transcribe audio data quickly and with a high degree of correctness. This speeds up the analysis process and allows researchers to center more of their period and energy on the interpretation of the data rather than the labor-intensive transcription process. Consequently, automatic transcription is becoming increasingly popular in qualitative research methodology.