Take the aTrain. Introducing an interface for the Accessible Transcription of Interviews

Armin Haberl, Jürgen Fleiß, Dominik Kowald and Stefan Thalmann

Journal of Behavioral and Experimental Finance, 2024, vol. 41, issue C

Abstract: Research in behavioral and experimental finance becomes more multifaceted and the analysis of data from speech interactions more important. This raises the need for technical support for researchers using qualitative data generated from speech interactions. aTrain serves this need and is an open-source, offline transcription tool with a graphical interface for audio data in multiple languages. It requires no programming skills, runs on most computers, operates without internet, and ensures data is not uploaded to external servers. aTrain combines OpenAI’s Whisper transcription models with speaker recognition and provides output that integrates with MAXQDA and ATLAS.ti. Available on the Microsoft Store for easy installation, its source code is also accessible on GitHub. aTrain, designed for speed on local computers, transcribes audio files at 2-3 times the audio duration on mobile CPUs using the highest-accuracy Whisper transcription models. With an entry-level graphics card, this speed improves to 30% of the audio duration.

Keywords: Transcription; Local; Whisper; AI; Machine learning; Qualitative research; Interview transcription; Qualitative data analysis (search for similar items in EconPapers)
JEL-codes: C65 C88 Z19 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:beexfi:v:41:y:2024:i:c:s2214635024000066

DOI: 10.1016/j.jbef.2024.100891

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