This article addresses the implications of transcriptions for scientific knowledge by focusing on automatic transcription software called speech-to-text. The article presents the general functioning and uses of speech-to-text software, then focuses on the evaluation of a specific software conducted by the author as a social scientist. This evaluation allows one to open the black box of the software by determining in a qualitative way the sources of its systematic errors. While the software undoubtedly provides a reliable semantic environment, it encounters two types of problems of a distinct nature that are intertwined in the computational literature: those generated by the limitations of the software's computational models, which can be solved by improving the system's models, and those related to ordinary conversation of a praxeological nature, which remain beyond the machine's reach. A detailed comparison with transcriptions manually performed in the manner of conversation analysis shows how the software makes interaction disappear from its transcriptions.
https://journals.openedition.org/rac/27984