Conducting “manual” transcriptions and analyses is unsustainable for most historical oral archives because they require a remarkable amount of funds and time. The FONTI 4.0 project aims at exploring the suitability of automatic transcription and information extraction technologies for making historical oral sources available. In this work, we conducted an experiment to test the performance of two commercial speech-to-text services (Google Cloud Speech-to-text and Amazon Transcribe) on digitized oral sources. We created an eight-hour corpus made of manually transcribed and annotated historical speech recordings in TEI format. The results clearly show how audio quality and disturbing elements (e.g., overlaps, foreign words, etc.) impact on the automatic transcription, showing what needs to be improved for implementing an unsupervised transcription chain
