Where might we explore the potential of digital convergence in ways that provide catalysts to individual creativity, plurality of thought and representation, and at the same time benefit from the obvious efficiency gains from using the computer as a digital hub for the entire research process?
In his side-by-side comparison of the listen-and-type method versus voice recognition software, Johnson (2011) provides a good example of what Brown's question might look like in practice. Johnson's research note is a measured and systematic exploration of the affordances and constraints of a new technology. Despite his strange conclusions about hiring a graduate student to "intelligently transcribe" using a combination of both approaches (p. 96), Johnson provides a service to researchers who might be curious about voice recognition software but who don't have the time or the means to take the plunge.
Regarding the ability of voice recognition software to ease "mental comfort," Johnson said, "My initial amazement at the software's work quickly wore off and I found both means of transcription equally dull" (p. 95). You have to wonder that if transcription is indeed the qualitative researcher's first interpretive act, then why is he so bored with his own data? Nonetheless, his findings underscore that "new and digital" does not always equate to "better and more efficient."
Regarding the ability of voice recognition software to ease "mental comfort," Johnson said, "My initial amazement at the software's work quickly wore off and I found both means of transcription equally dull" (p. 95). You have to wonder that if transcription is indeed the qualitative researcher's first interpretive act, then why is he so bored with his own data? Nonetheless, his findings underscore that "new and digital" does not always equate to "better and more efficient."
Putting aside the as-yet-unproven voice recognition software, computers have made a significant impact on the listen-and-type method. If used judiciously and reflexively, digital tools for transcription can live up to Brown's standard of improving efficiency while supporting flexible, open-ended, and inductive inquiry. For example, it is possible do download audio files from a digital microrecorder into transcription software on the computer and listen and type in one integrated interface using keystrokes to pause, rewind, and so on. This is hugely efficient in itself, as it is now easy and inexpensive to archive, share, and transport digitized transcripts.
But my big take-away this week is learning that certain software, particularly Inqscribe, will allow me to synchronize my subsequent readings of the transcripts with the audio, something I have never tried to do systematically. I created the transcripts, and then the audio files went into a folder, never to be heard from again. Because I was never meticulous enough to manually insert timestamps into the transcripts, it was always tedious and cumbersome to locate a specific excerpt in the audio when I had to. Inqscribe enables timestamping with two keystrokes, and when clicked, the timestamp takes you to the precise location within the audio. I am looking forward to trying this function in upcoming transcription projects.
The synchronized transcripts have changed my life in terms of research with audio data. Seriously.
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