Research Transcription: Readable Is Not the Same as Useful

When the Transcription Becomes the Data

Researchers use interview transcriptions for much more than just remembering what was said.

They use them to:

• Code responses
• Identify themes
• Compare participants
• Select quotations
• Analyze language
• Support findings
• Create hypotheses
• Draw conclusions
• Create publications and reports

When researchers work from the transcription instead of repeatedly listening to the recording, they rely on the written text to represent the participant's words.

That makes transcription accuracy essential to the research process. [1][4]

The researcher must ask themself, “Can I rely on this transcription as research itself?”

Not All Errors Are Equal

Some transcription errors have a greater effect than others.

If a participant says:

“I went to the clinic on Tuesday.”

and the transcription says:

“I went to the clinic Tuesday.”

the meaning probably has not changed.

But consider:

“The medication did help.”

versus:

“The medication didn't help.”

One word changes the participant's meaning completely.

The same problem can occur with medical terminology, names, numbers, dates, acronyms, or other words that carry important meaning within the study.

AI companies love to use Word Error Rate Scores. And, under certain conditions, some achieve high scores. But some mis-hears can completely skew the researcher’s data. [2][6]

Speaker Diarization - What It Is and How It Matters

Speaker diarization is the process of determining who spoke when. More commonly known as speaker identification, it is essential when more than two people are involved in a recording. [8]

Consider a focus group.

One participant describes a positive experience with a treatment program. Another participant describes a negative experience.

If their statements are assigned to the wrong speakers, every word could be transcribed correctly, yet the transcription could still misrepresent the discussion and skew the findings.

Speaker mislabelings become more common when people interrupt each other, speak at the same time, have similar voices, or respond with short statements such as:

“Yes.”

“Exactly.”

“That happened to me too.”

In qualitative research, who said something can be just as important as what was said.

Real Interviews Are Not Controlled Recordings

Research interviews rarely sound like carefully recorded dictation, like from a doctor.

People pause.

They change direction in the middle of a sentence.

They use abbreviations.

They speak quietly.

They laugh.

They interrupt each other.

They use technical language.

They may have regional or international accents.

The interviewer may speak while the participant is still answering.

And sometimes the recording itself is simply difficult to hear.

These conditions create ambiguity. A transcription system or transcriptionist has to determine what was actually said without changing the participant's meaning. Recording quality and conversational conditions can materially affect transcription quality. [3]

That is where context becomes important.

Context Can Resolve What Sound Alone Cannot

Human language includes words and phrases that sound alike.

A trained transcriptionist can listen to the surrounding discussion and use context to determine which interpretation makes sense. They draw from knowledge and experience.

This is particularly important in healthcare and research interviews, where a single recording may include medication names, diagnoses, abbreviations, unique terminology, program names, and specialized research language.

When something remains unclear, an experienced transcriptionist does not simply guess.

They flag it for review.

That distinction matters.

An obvious [inaudible] or uncertain word tells the researcher that something needs attention.

A confident-looking incorrect word does not.

Quotations Require a Higher Standard

Direct quotations deserve particular attention because researchers may reproduce a participant's words in reports, presentations, or publications. Researchers commonly use quotations as evidence to support qualitative findings. [7]

If the quotation is important enough to publish, it is important enough to verify.

That means reviewing the relevant audio even when the rest of the transcription is sufficiently accurate for coding or general analysis.

The required level of review should therefore depend on how you will use the transcription. [5]

How Accurate Does It Need To Be?

No single transcription method fits every research project.

A researcher using a recording simply to create meeting notes may accept a quick draft from an AI transcription service or overseas freelance worker, but if the transcription will be coded and quoted in a published study, they will seek a service with higher quality control.

The standard should match how much the research depends on exact wording and correct speaker attribution. As that dependence increases, so does the need for careful review. [1][5]

Percentages Can Be Misleading

Transcription companies often advertise accuracy percentages such as 95%, 98%, or 99%.

Those numbers can sound reassuring. And they can drive phone calls to the transcription company.

But without knowing how accuracy was measured, what recordings were tested, and which errors were counted, the percentage doesn't reflect how a service will perform on a specific interview. The “Word Error Rate,” for example, measures word-level discrepancies but does not reflect human judgment or the severity of an error. [6]

And what about poor audio?

What does the transcription provider do when the recording is difficult?

Does someone review unclear language?

Are technical terms researched?

Are speakers checked?

Are uncertain words flagged instead of guessed?

Is the completed transcription cross-proofed by another transcriber before delivery?

These processes tell researchers more about the reliability of the final transcription than a marketing percentage alone.

Making The Right Choice

There is a place for all types of transcription services. For non-confidential drafts, AI or a transcription service that uses overseas freelancers both offer fast, inexpensive options.

But for confidential research, where the stakes are higher, specialization brings necessary emphasis to non-negotiable areas: quality control and security.

If the researcher will code the transcription, compare participants, extract quotations, or use it to support findings, readability is not enough.

The transcription needs to preserve the participant's meaning.

A good transcription should not just be easy to read. It should be dependable enough for what the researcher plans to do with it.

For information on how Research Transcriptions uses a 100% human process to deliver accurate transcription you can rely on, get in touch with us. 

References

[1] Poland BD. Transcription Quality as an Aspect of Rigor in Qualitative Research. Qualitative Inquiry. 1995;1(3):290-310. doi:10.1177/107780049500100302. https://journals.sagepub.com/doi/10.1177/107780049500100302

[2] Clark L, Sanchez Birkhead A, Fernandez C, Egger MJ. A Transcription and Translation Protocol for Sensitive Cross-Cultural Team Research. Qualitative Health Research. 2017;27(12):1751-1764. doi:10.1177/1049732317726761. https://pmc.ncbi.nlm.nih.gov/articles/PMC5642906/

[3] Hennink M, Weber MB. Quality Issues of Court Reporters and Transcriptionists for Qualitative Research. Qualitative Health Research. 2013;23(5):700-710. doi:10.1177/1049732313481502. https://pmc.ncbi.nlm.nih.gov/articles/PMC4465445/

[4] Davidson C. Transcription: Imperatives for Qualitative Research. International Journal of Qualitative Methods. 2009;8(2):35-52. doi:10.1177/160940690900800206. https://journals.sagepub.com/doi/10.1177/160940690900800206

[5] Hagens V, Dobrow MJ, Chafe R. Interviewee Transcript Review: assessing the impact on qualitative research. BMC Medical Research Methodology. 2009;9:47. doi:10.1186/1471-2288-9-47. https://pmc.ncbi.nlm.nih.gov/articles/PMC2713273/

[6] Whetten R, Kennington C. Evaluating and Improving Automatic Speech Recognition using Severity. Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks. 2023:79-91. doi:10.18653/v1/2023.bionlp-1.6. https://aclanthology.org/2023.bionlp-1.6/

[7] Yeo S, Han S. Which Quotations to Use?: Guidance on Selecting and Reporting Quotations in Qualitative Research. International Journal of Qualitative Methods. 2025;24. doi:10.1177/16094069251353449. https://pmc.ncbi.nlm.nih.gov/articles/PMC12362350/

[8] Anguera X, Bozonnet S, Evans N, Fredouille C, Friedland G, Vinyals O. Speaker Diarization: A Review of Recent Research. IEEE Transactions on Audio, Speech, and Language Processing. 2012;20(2):356-370. doi:10.1109/TASL.2011.2125954. https://ieeexplore.ieee.org/document/6135543/