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

Armin Haberl*, Jürgen Fleiß, Dominik Kowald, Stefan Thalmann*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number100891
JournalJournal of Behavioral and Experimental Finance
Volume41
DOIs
Publication statusPublished - Mar 2024

Keywords

  • AI
  • Interview transcription
  • Local
  • Machine learning
  • Qualitative data analysis
  • Qualitative research
  • Transcription
  • Whisper

ASJC Scopus subject areas

  • Finance

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