Although it is not necessary to master Python, you will need to have Anaconda installed on your computer (or Python on Linux and MacOS). In this tutorial, we provide a script written in Python. Good news: it takes only a few lines of code. This tool is not a substitute for careful listening, but overall, it brings down the time spent typing text: once the text has been transcribed by the machine, all that is left to do is listen to the interview and check for transcription errors, or assign each statement to a speaker. Six model “sizes” are available, from “tiny” to “large-v2”, transcription quality increasing with the size of the model (as does computing time). It is based on an artificial neural network trained on several hundred thousand hours of transcribed recordings, in dozens of different languages (details available here). OpenAI’s Whisper is a free automatic speech recognition software.
This tutorial introduces a free tool to transcribe interviews fairly quickly and with remarkable quality, even in such “noisy” scenes. it is then difficult to avoid a manual transcription. They perform even worse when the recording is marred by background noises – a quite ordinary situation for ethnographers who carry out their craft in coffees shops, parks, in the interviewee’s living room with the TV playing in the background, etc. Most give error rates of over 55% for spontaneous discussions 1, and some come with a hefty price tag. There are, of course, dozens of transcription services that claim to automatically render audio interviews into text, yet their results are far from perfect. And while the transcription process can often be serendipitous, it is also notoriously tedious work.
They may be used to collect oral history, during the course of ethnographic research, or for panel interviews. Recorded interviews are a classic element in the social scientific toolbox.
BERNIE SANDERS ANACONDA VIDEO HOW TO
Tips for getting started, and some thoughts on how to use it
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