Nowadays, in the field of digital humanities and ethnomusicology, the preservation and analysis of traditional European folk music presents unique challenges and opportunities. This paper introduces an innovative Artificial Intelligence (AI) system designed to address these challenges by digitizing performances of traditional European folk music. Employing artificial intelligence techniques, the system processes pre-recorded video performances to extract crucial musical information, including the transcription of audio into musical scores and, where applicable, the transcription of lyrics. The core functionality of this system leverages state-of-the-art techniques in machine learning in the area of audio processing, enabling the interpretation and transcription of complex musical compositions and vocal performances. The aim of this research is to contribute significantly to the preservation and accessibility of traditional folk music, highlighting the potential of AI in ethnomusicology and digital humanities. This paper details the proposed system’s architecture, methodologies for audio and video processing, and the challenges encountered in capturing the nuances of traditional folk music. Preliminary results of the system on a digital archive of traditional music from Portugal are presented, and the effectiveness and drawbacks of the system in producing detailed and accurate musical and lyric transcriptions are discussed. The tool is publicly available for musicians, scholars, and enthusiasts of traditional European folk music.