Can data teach us how to listen?

We start with one madrigal, one jazz phrase, and one hit song—then ask what changes when we compare hundreds more.

Each movement has its own background track. Playing an example lowers the soundtrack; it returns when the clip ends.

Why compute music?

Why compare one musical passage with an entire corpus?

Many musicological arguments begin with something a listener notices: a charged word, a familiar phrase, the lift of a chorus. Digital scores and transcriptions let us check whether that moment is exceptional or part of a larger habit.

Counting gives us firmer ground for interpretation. We can ask how often a pattern occurs, where it appears, and whether it still appears when we change the rules used to find it.

01 · text + scoreDoes meaning leave a repeatable musical trace?

We compare how Monteverdi sets expressive words and ends lines of poetry.

02 · performed notesCan improvisers share language without sounding alike?

We track short interval patterns across transcribed solos and compare each player’s vocabulary.

03 · songs + timeDoes a cultural trend survive a wider history?

We revisit a published trend over a longer period, then compare verses and choruses within the same songs.

Our approach Start with something audible, decide how to measure it, check the rest of the corpus, and see how the result changes under different choices.

Loading Monteverdi evidence…

In Monteverdi, the notes were fixed in a score.

What changes when the notes are improvised?

The evidence now comes from recorded solos, but we still begin with a phrase we can hear and then search for it across a corpus.
Loading the jazz vocabulary…

The jazz study compares musicians.

The pop study compares years.

We move from short phrases inside solos to changes across seventy-two years of popular songs.
Loading the pop timeline…

Where could this research go next?

Each result leaves us with a new question.

The measurements can be reused in other repertories, but they need more historical evidence and more listening before they can support broader claims.

Text + score

Do other composers mark poetic lines this way?

We could repeat the boundary analysis in sacred music, opera, and later song, then compare the written score with recorded performances.

Needed next: more composers, translations, and score-aligned recordings.
Performance + network

Can we trace where a lick traveled?

Dates, teachers, bands, and cities would help separate a widespread convention from a phrase that may have passed between musicians.

Needed next: social histories, session personnel, and phrase-aligned audio.
Culture + markets

What changed pop songwriting?

Song features could be linked to radio formats, label concentration, streaming incentives, and changes in release strategy. That would let us study specific shifts rather than treating the calendar year as a cause.

Needed next: platform and industry data, plus a causal research design.
Listeners + validation

Can listeners hear the measured differences?

A listening study could test whether people hear the poetic boundary, recognize a transposed interval pattern, or identify a chorus from melody alone.

Needed next: listener responses and carefully matched audio examples.
The broader stake

Digital archives let us revisit familiar stories at a larger scale. They also inherit the limits of what was preserved and encoded, so the makeup of the corpus must remain part of the argument.

What did the three methods show?

In every study, the larger corpus changed what we could claim about the original example.

word → lineMonteverdi

Some meanings receive recurring treatment, and poetic line endings consistently receive more time.

lick → playerJazz

Players share recurring interval patterns, but the strength of a connection depends on how a lick is defined.

song → historyPop

A trend that looks clear over thirty years can bend or disappear when we add four more decades.

We began by listening for a detail. The data told us where else to listen—and, just as often, when our first impression needed revision.
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HUMA UN1123 · Music Humanities