TY - JOUR
T1 - Take the aTrain. Introducing an interface for the Accessible Transcription of Interviews
AU - Haberl, Armin
AU - Fleiß, Jürgen
AU - Kowald, Dominik
AU - Thalmann, Stefan
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/3
Y1 - 2024/3
N2 - 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.
AB - 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.
KW - AI
KW - Interview transcription
KW - Local
KW - Machine learning
KW - Qualitative data analysis
KW - Qualitative research
KW - Transcription
KW - Whisper
UR - http://www.scopus.com/inward/record.url?scp=85183200374&partnerID=8YFLogxK
U2 - 10.1016/j.jbef.2024.100891
DO - 10.1016/j.jbef.2024.100891
M3 - Article
AN - SCOPUS:85183200374
SN - 2214-6350
VL - 41
JO - Journal of Behavioral and Experimental Finance
JF - Journal of Behavioral and Experimental Finance
M1 - 100891
ER -