![]() I recorded nine interviews, which ranged from 18-48 minutes, and in which there was one participant, the primary interviewer, and myself. My aim was to speed up my transcription process, and to remove the frustration that normally accompanies this step in the research process for me. I reviewed three different options and services, ultimately using one of them throughout a current project. The same machine-learning technology can be used to transcribe interviews. Google Duplex takes this further and is almost indistinguishable from a human assistant. So much so, that Siri, Alexa, Cortana, and Google Home are now part of life for millions of people. ![]() Where previously, voice-activated systems and voice-to-text applications were stuck at low levels of accuracy and speed, the use of machine learning has resulted in a variety of devices and services that boast of 95% and higher accuracy. The advent of machine learning represents a dramatic change in the effectiveness and efficiency of voice-to-text software. How MAXQDA’s Transcription Mode Feature Can Be Used in Conjunction with Machine Learning Voice-to-Text Services As a result, transcribing a 30-minute audio file takes me several hours, and by the end, I am exhausted. My typing is too slow, my working-memory too short, and I get confused between the function keys and buttons. Even with the many functions available in MAXQDA’s Multimedia Browser, such as keyboard shortcuts and automatic speaker changes, I am still far too clumsy with hitting F4, the pause button, or the various other buttons, to transcribe the audio efficiently. The software is not, however, able to make us efficient in transcribing audio files. Guest article by Matthew Loxton, a Principal Healthcare Analyst and Professional MAXQDA Trainer.įor some people, such as myself, MAXQDA’s Transcription Mode tools are a wonderful help.
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