Marking musical dictations using the edit distance algorithm

Musical dictations for ear training and training in music writing form a key practice of basic musical training. Marking students' dictation exercises for large groups of students can require a lot of work. In this paper, we present a tool, called CADiM, that can help automate the marking of such musical dictations. The edit distance, which computes the similarity between any two strings, has been used in various areas such as string/text analysis, protein/genome matching in bio‐computing and musical applications, for example music retrieval or musicological analysis. CADiM's marking algorithm is based on an earlier edit distance proposed for musical sequences, but adapted to reflect the marking heuristic used by a domain expert's specific approach to musical training. Computing an edit distance on musical scores requires using an appropriate representation. More precisely, given our specific context, a symbolic representation is required. We use MusicXML, an XML application for standard Western music notation. Given a Document Type Definition for MusicXML, existing Java tools can generate a MusicXML parser. Such a parser, given appropriate input files, then generates an intermediate form (DOM object) on which analyses and transformations are performed in order to compute the edit distance. In turn, the edit distance is used to give a mark as well as identify the key errors. CADiM has been applied to a number of test cases and the results compared with those obtained by a domain expert. Overall, the results are promising, namely, only 3% difference between the domain expert's marks and those produced by CADiM. Copyright © 2006 John Wiley & Sons, Ltd.