Robust Segmentation and Annotation of Folk Song Recordings

Even though folk songs have been passed down mainly by oral tradition, most musicologists study the relation between folk songs on the basis of score-based transcriptions. Due to the complexity of audio recordings, once having the transcriptions, the original recorded tunes are often no longer studied in the actual folk song research though they still may contain valuable information. In this paper, we introduce an automated approach for segmenting folk song recordings into its constituent stanzas, which can then be made accessible to folk song researchers by means of suitable visualization, searching, and navigation interfaces. Performed by elderly non-professional singers, the main challenge with the recordings is that most singers have serious problems with the intonation, fluctuating with their voices even over several semitones throughout a song. Using a combination of robust audio features along with various cleaning and audio matching strategies, our approach yields accurate segmentations even in the presence of strong deviations.