![]() Words are ordered in terms of the frequency that they are mentioned, and It has finished processing the conversation after recording. ![]() It displays these as a list under the title once I'll discuss each of these below alongside some limits/considerations. I found the following features particularly useful: 1) the generation of automatic word frequencies and word clouds 2) ability to explore the transcript and highlight key words 3) ease of editing the transcript. you can also feed-in pre-recorded audio into the application, which then generates a transcript). Having a conversation automatically transcribed in real-time is a huge advantage (NB. I've used this recording as it gives a good indication of how Otter.ai can be used in a mobile and group setting, also demonstrating its ability to integrate photos to provide more information/context to the conversations. The voices of several people (we were in a big group) as we move around the exhibition, talking about different historic and contemporary maps. Recording was taken (with permission) during a guided tour with StewartĪckland from the Map Department at the Bodleian Library - it captures For the example in this post, I've used an excerpt from a recording taken on my smartphone at the Talking Maps exhibition at the Weston Library in Oxford (fascinating exhibition!). I've used Otter.ai for a while in my PhD research to record, transcribe, edit, and summarise qualitative interviews. ![]() You can also check out this third post which covers some ethical, privacy/security, and safe storage considerations for qualitative research. Introduction to using speech-to-text apps (see part 1 for background information and an overview of what's available in 2020). ![]() I highlight some key features, provide examples, and briefly discuss some key considerations. This blog post is an overview and tutorial for using automated transcription app ( Otter.ai) for qualitative research.
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