Manuals and Tutorials
Licences and Pricing
Site and group licences
Analyzing Qualitative Data
January 22, 2016
Audio and video give you a level of depth into your data that can’t be conveyed by words alone, letting you hear hesitations, sarcasm, and nuances in delivery that can change your interpretations of what your participants say. Yet most researchers and students will want to have typed transcripts of their qualitative interviews.
Text gives many advantages during the qualitative analysis process. You can read or skim read text much faster than you can listen to audio, and your eyes are good at quickly picking out keywords. Transcribed text can also be searched for keywords or synonyms, taking you directly to that point in the text.
It’s also easier to code text than multimedia data, and since most research outputs (especially journal articles, a thesis or book) tend to remain stubbornly text-based, including quotes is a standard way to embed qualitative data. Text can also be analysed in other ways, including statistical analysis and automated sentiment analysis.
Even when working primarily with the video or audio of qualitative interviews, most academic researchers and students will still generate a transcript for these reasons. But at the moment, there is no software that can reliably understand untrained interview audio, find words or create automatic transcriptions. Either the researcher themselves, or often an experienced transcriber will have to listen to the audio and type it up word for word.
Thus BEFORE starting interviews, it is worth considering a few ways to make sure that transcription goes smoothly, and cheaply. Finding a transcriber or transcription service is a key part of most qualitative research. But how much will it cost?
Well, this depends on the level of detail required. Verbatim transcriptions, especially when there is a need to capture the nuance of the conversation, are very time consuming to produce. These will capture not just the conversation word for word, but also every um, er, pause and hesitation, and sometimes even infliction. When there are gaps or pauses these will be detailed (such as [pause 5 sec]). This level of detail is illuminating, especially for discourse analysis, but expensive. Often researchers would like regular timestamps included (say at the top of each page) so that it is easy to find the position of the text in the audio. This also increases cost.
Often you will hear the phrase ‘Intelligent Verbatim’ used by transcription services, which denotes a middle ground where the transcriber chooses which pauses and detail are relevant, but is careful to make sure that the exact wording of the dialogue is recorded. This is what most qualitative research projects use, unless there is a methodological need for more detail.
This is still more detailed than what you would get from a standard typing service used in business, where phrases and words may be approximated. These services, sometimes called a ‘clean transcript’ are cheaper and easier to read (since they don’t have breaks or interjections, they are much more like reading dialogue from a novel), but generally lack the rigour and specificity for qualitative analysis. If someone said ‘afraid’ or ‘anxious’ it might represent a difference in your interpretation, so the exact words uttered must usually be noted. For more discussion, there is an interesting paper by Halcomb and Davidon (2006).
If you are conducting focus groups, this can also increase cost and difficulty because of the need to identify the different voices in the room. Typically this can add 20% to the transcription costs, some services will charge for each additional participant. Many transcribers will justifiably add an additional 20% or more for bad audio. We are going to look in the next blog post article about how to make sure this doesn’t happen, but noisy environments and bad recordings make the process much more time consuming, as it is necessary to keep going back and forward to correctly hear muffled words.
In general, you should expect to pay between £1 (often $1 in the States) at the absolute minimum and £3 ($2.70) per audio minute for transcription. This means a one-hour interview will cost around £80 ($60) to be transcribed, depending on the quality of the service and number of people speaking. For fast turnaround (ie within 24 or 48hrs) expect to pay a premium. After salaries, it is often the most expensive part of a qualitative research project. So if you have 20 interviews, you will need to budget £1600 ($1200). This is why many students end up doing transcription themselves, and while this is good for keeping close to your data, it is not easy, and can be a false economy.
As someone who has also done transcription before, it is vital to stress what a difficult and specialist job this is. Almost no-one can type at the same speed that people speak, and so the work takes much longer than the length of the interview. You are not paying someone £60+ an hour, they will work two or three times that long to get everything typed and corrected. It is also exhausting, and mentally draining. I’ve tried automated software for transcription, like Dragon Dictate or Microsoft’s Project Oxford, but these are not yet geared up for this type of work. They struggle with words that run together, require perfect audio recordings with no extra noises, and can’t identify different voices. I know some transcribers that use trained dictation software in their work: the computer recognises their own voice, so they have to listen with headphones to the audio and clearly repeat every word, one by one.
There are many online services offering transcription services, easily found with a quick Google search. I don’t have any specific ones to recommend at the moment, but if you want to use a company I would suggest you choose one that specifically works with research interviews, and offers the options above. It is also a good idea to choose one that works in your native dialect! If you are not used to hearing British, Scottish or Indian accents as an American transcriber (or vice versa), there can be odd misunderstandings and discrepancies that arise.
A transcriber that is used to working in your field of study is also useful: they will spot commonly used terminology and abbreviations. My favourite transcriber had worked in a medical field before, so was used to most of the NHS acronyms, and if there were terms or phrases he hadn’t come across before, he would Google them to make sure they were right. Good people like this are hard to come by!
Personally, I have always used a few freelance transcribers who work exclusively with universities. Ask your department or colleagues for local recommendations, and if part of a research project, one who is already on the university payroll system can save major headaches and delays. Don’t be afraid to give a new transcriber just one transcript to see how they do, before you commit yourself to giving them all the work. It’s also not a bad idea to have a back-up, especially if a transcriber gets sick, or you need a large batch of transcripts in a hurry.
Finally, there will always be errors and uncertainties. You still need to have at least a cursory read through of the transcript to make sure it makes sense and there aren’t typos. A feedback loop is a valuable thing to set up with a good transcriber, so they can learn about common phrases and terms they are mishearing, and the accuracy will improve. Words misheard will usually be marked with [inaudible] and you will need to go through and fix these. Often, it will be obvious to you as the researcher who was there in the room, but not for someone else, especially when it occurs just as the noisy expresso machine turns on!
I hope this is illuminating, it’s one of those things that is difficult to find much written advice on. Very few articles discuss this essential part of the research process – Davidson 2009 is a notable exception. Check out some of our other blog post articles for more on this stage, including how to get good quality recordings, and 10 tips for qualitative interviewing, and let us know if you have any suggestions or tips of your own!
Once you’ve got a transcript, you will be ready to start qualitative coding your text data, and Quirkos is an ideal software tool to bring your interview and focus-group data to life, with a visual and intuitive interface. Download a free trial, or watch a video overview showing you how to start a new analysis project in just 20 minutes.