Tessa

Tessa automates tessitura analysis from MusicXML-encoded digital scores to quantify the habitual pitch range of musical pieces and roles.

Key Features:

• MATLAB implementation: Implemented in MATLAB and converts MusicXML files into MATLAB-compatible structure arrays (MAT) for analysis.
• MusicXML conversion: Converts digital sheet music in MusicXML format into MAT files to enable programmatic data access.
• Data extraction: Extracts pitch, duration, and lyrics and saves these as arrays for downstream analysis.
• Metadata handling: Captures tempo, score part number, and piece title alongside musical data.
• Statistical analyses: Generates histograms, box plots, and descriptive statistical evaluations of tessitura data.
• Comparative analysis: Enables comparison of tessitura distributions with voice range profiles or other assessment tools.

Scientific Applications:

• Repertoire assessment: Quantifies tessitura to assess suitability of musical pieces or roles for specific singers.
• Vocal pedagogy and training: Supports comparison of tessitura data with voice range profiles for vocal training and repertoire selection.
• Performance planning: Informs pacing and programming decisions for extended performances based on tessitura demands.
• Musicological analysis: Enables comparative analysis of vocal demand across songs or cycles by quantifying habitual pitch ranges.

Methodology:

Converts MusicXML files into MATLAB-compatible structure arrays (MAT), extracts pitch, duration, lyrics, and metadata (tempo, score part number, piece title), then computes histograms, box plots, and descriptive statistical measures of tessitura.