  Manual melody detection is a tedious task requiring high expertise level,
while automatic detection is often not expressive or powerful enough. Thus, we
present MelodyVis, a visual application designed in collaboration with
musicology experts to explore melodic patterns in digital sheet music.
MelodyVis features five connected views, including a Melody Operator Graph and
a Voicing Timeline. The system utilizes eight atomic operators, such as
transposition and mirroring, to capture melody repetitions and variations.
Users can start their analysis by manually selecting patterns in the sheet
view, and then identifying other patterns based on the selected samples through
an interactive exploration process. We conducted a user study to investigate
the effectiveness and usefulness of our approach and its integrated melodic
operators, including usability and mental load questions. We compared the
analysis executed by 25 participants with and without the operators. The study
results indicate that the participants could identify at least twice as many
patterns with activated operators. MelodyVis allows analysts to steer the
analysis process and interpret results. Our study also confirms the usefulness
of MelodyVis in supporting common analytical tasks in melodic analysis, with
participants reporting improved pattern identification and interpretation.
Thus, MelodyVis addresses the limitations of fully-automated approaches,
enabling music analysts to step into the analysis process and uncover and
understand intricate melodic patterns and transformations in sheet music.
