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This report describes a publicly available dataset of harmonic analyses of all Beethoven string quartets together with a new annotation scheme. The quantitative study of large datasets is gaining increasing importance in musicology, reflecting a global trend toward empirical corpus studies and big data methods in the sciences as well as the (digital) humanities. Several initiatives and publications exemplify these new developments (e.g., Mauch et al., 2007; Rohrmeier and Cross, 2008; Temperley, 2009; De Clercq and Temperley, 2011; Schubert and Cumming, 2015; Klauk and Zalkow, 2016; White and Quinn, 2016). Ever increasing digital music resources are available online in the form of large collections of audio recordings,1 scanned scores,2 or MIDI files.3 Furthermore, musicologists have produced collections of symbolic and audio music repositories, e.g., the Essen Folksong collection (Schaffrath, 1995), the score collection in Humdrum/KERN format4 (Huron, 1997; Sapp, 2014), and the corpora of audio resources of Non-Western classical music traditions gathered by the CompMusic project5 (Serra, 2014). However, raw audio or symbolic musical information is often insufficient to investigate more abstract structural properties of musical styles, such as harmony, counterpoint, or form. Sufficiently sophisticated and statistically fully reliable automated Music Information Retrieval (MIR) methods for structural inference are not yet available. Despite the availability of raw audio material and the recent research initiatives mentioned above, digital musicology still lacks large labeled corpora combining score and harmonic annotations. These corpora are necessary as ground truth data for the minute investigation of structural dimensions of music such as harmony. As we elaborate below, our research addresses this gap by providing a large dataset of expert-generated harmonic labels in the stylistically coherent corpus of Ludwig van Beethoven’s string quartets, the Annotated Beethoven Corpus (ABC). This corpus will be useful for the research purposes of empirical and digital musicology, such as deepening the understanding of musical syntax, voice-leading schemata, form, and style, as well as for the development and evaluation of computational models of harmony and musical structure in general.

The Annotated Beethoven Corpus (ABC): A Dataset of Harmonic Analyses of All Beethoven String Quartets