expertise / music theory

Music theory training data. Notes are easy. Why they work is not.

A generation model can produce a chorale with parallel fifths in every phrase and never know. eeko commissions music theorists, composers, arrangers, and performers to label harmony and form, align notation to audio, write original works, and grade generated music, with rights recorded on every item and a second musician on every label.

Two musicians on every item Rights recorded per recording Pilot batch before volume Reply inside one business day
Hero image · 840 × 1050
reviewers per item
2mus
the analyst, then a second musician
first delivery
1pilot
a paid pilot batch before any volume order
delivery formats
6fmt
JSON Lines, CSV, Parquet, WebDataset, COCO, Croissant
reply time
1day
a data lead who has read the brief

What is music theory training data?

Music theory training data is music with the analysis attached. A score or recording where the key, every chord, every cadence, and every modulation is labeled. Part-writing marked for the techniques it uses and the errors it contains. Sections, phrases, and themes bounded across a whole piece. Notation aligned to a MIDI file or a live recording at the level of individual notes. And generated music graded by a musician who can say exactly what is wrong with bar seven.

Models trained on raw audio learn what music sounds like and nothing about why. The symptoms would get a first-year theory student marked down: chords named in the wrong key, cadences that never resolve, a meter the model has misread, MIDI that drifts out of step with the score halfway through, and generated pieces that wander without form. The audio usually comes from sources with disputed rights, too.

eeko's data practice addresses both problems at once: trained musicians label to a written scheme, a second musician checks every item, and every recording, score, and composition carries a consent and licence record from the creator who holds the rights. It is one field within our AI training data practice, sourced like our speech and audio datasets and licensed on the terms of our AI data licensing.

Aligned analysis image · 2100 × 900
One passage, three layers: the score with Roman numerals and cadences, the phrase structure, and the recording aligned beneath it at the note level, each label attributed to the musician who placed it.

Music data for AI, from harmony to commission.

Six lines of work, scoped by style, instrumentation, and format, and proven on a pilot batch. Order one layer on music you hold the rights to, or commission music and analysis together.

01 / harmonyCORE
Harmonic analysis
Roman numeral and functional analysis, with the key, each modulation, every cadence, and non-chord tones labeled, aligned to the score and to the audio, under a scheme that fixes how ambiguous passages are handled.
02 / voice-leadingCORE
Voice-leading annotation
Part-writing marked for techniques and errors, from chorale textures to jazz voicings and string quartet writing. Parallel fifths, doubled leading tones, and voice crossing tagged where they occur.
03 / alignmentCORE
Score, MIDI, and audio alignment
Notation aligned to MIDI and to live performances, note by note or beat by beat, with tempo changes, rubato, ornaments, and expressive timing marked.
04 / formCORE
Form and structure labels
Section, phrase, theme, and formal-type labels that span a whole piece, for models that need to hold a structure over minutes rather than bars.
05 / commissionNEW
Original compositions and arrangements
New works and arrangements written to your brief by composers in the network, delivered as score, MIDI, and stems, under licence terms stated in the job and bound to each item.
06 / judgmentEVAL
Graded judgments of generated music
Musicians compare and score generated pieces for harmony, part-writing, form, and fit to the requested style, and write the rationale. Built for preference training and for evaluating one model version against another.

What a music model gets wrong and a theorist marks in red.

Invisible to a loss curve, obvious to anyone who has taught a theory class. Our analysis scheme and grading rubric are organized around them.

Grading image · 1200 × 900
A generated chorale under review: the parallels circled, the cadence that never arrives noted, the rationale written for the record.

Six errors the analysis scheme is built around

  • Parallel fifths and octaves — the most basic part-writing error, produced confidently and at scale.
  • The wrong key — chords labeled relative to a tonic the passage left two bars ago.
  • Cadences that do not land — phrases that stop rather than resolve, because the model never learned what a cadence is for.
  • Misread meter — a passage in three analyzed as if it were in four, with every downbeat displaced.
  • Alignment drift — a score and a recording that agree at bar one and are a beat apart by bar forty.
  • Music without form — a generated piece that wanders, never returns, and ends because the token budget ran out.

Paid remote work for musicians, between seasons.

The eeko expert network pays theorists, composers, arrangers, and performers to analyze, align, compose, and review. Rate, scope, deadline, and the licence terms for anything you compose are on every job before you accept it.

who we look for
Trained ears, written-down reasoning

You do not need every item below. A theory-strong music degree or a professional portfolio is enough to start receiving matching jobs.

  • Degree Music theory, composition, or performance
  • Advanced study Graduate work or teaching experience in theory
  • Professional work Composer, arranger, copyist, orchestrator, or transcriber
  • Tools Fluent in notation software and MIDI
  • Styles Common-practice, jazz, film, popular, or other specialisms
what the jobs involve
Your analysis, to a scheme, with a second pair of ears

Written scheme or rubric on every job, a second musician on every item, and approved work credited to your account automatically.

  • Analyze Keys, chords, cadences, voice leading, and form in scores and recordings
  • Align Notation to MIDI and to performances, drift corrected
  • Compose Original works or arrangements to a brief, with score, MIDI, and stems
  • Grade and review Judge generated music, or check a colleague's analyses before delivery

Rights, fingerprints, and review on every recording.

Music carries more disputed rights than almost any other training material, and analysis is interpretive. Both need a record that satisfies a licensing lawyer and a second theorist.

Licensed or composed new

Every recording, score, and composition is licensed from the creator who holds the rights, with consent and licence attached to that item, or written by a musician in the network under terms stated in the job. Nothing comes from a streaming rip or a sheet music library.

Fingerprinted and screened

Audio receives an acoustic fingerprint and a cryptographic hash on intake, with an independent timestamp, and is checked against the corpus for duplicates. Embedded metadata is read to confirm human origin and to catch generator signatures before a musician spends time on the file.

Attributed and receipted

Every label records who made it and who confirmed it, inside a hash-chained audit trail, and reviewer disagreements are logged rather than averaged. Delivery closes with a signed receipt naming each item by identifier and hash. The full method is on our verified human data page.

From a repertoire brief to a signed delivery.

Fixed price per accepted item, agreed on the pilot and held for production. Volume starts when your team has reviewed real output against the scheme.

STEP 01
Scope
Styles, instrumentation, label layers, source of music, formats, and licence terms. A data lead replies inside one business day with questions and a staffing view.
STEP 02
Scheme and pilot
We write the analysis scheme or grading rubric with you, including how ambiguous passages are handled, then deliver a paid pilot batch for your team to check.
STEP 03
Production
Verified musicians work in batches. A second musician reviews every item, disagreements are adjudicated and logged, and agreement is reported per delivery.
STEP 04
Delivery
Audio as WebDataset or Parquet, labels and alignment maps as JSON Lines or CSV, Croissant metadata, and a signed receipt. Standing orders extend the collection.

Music theory training data questions.

What is music theory training data?

Music theory training data is music with a musician's analysis attached: a score or recording with the key, chords, cadences, and modulations labeled, part-writing marked for its techniques and errors, and notation aligned to the audio note by note. Raw audio teaches a model what music sounds like; this teaches it why a passage works.

How much does music theory training data cost?

We price per accepted item, and the unit depends on the task. Labeling the harmony of a chorale phrase costs less than aligning a full orchestral score to a live recording, and an original composition is priced as a commission with its licence terms stated in the job. After scoping we quote a fixed price for a pilot batch, and the same unit price holds for production. Rejected items are not billed.

Who owns the rights to the music in the dataset?

Every recording, score, and composition is either licensed from the creator who holds the rights, with licence and consent attached to that item, or written new by a musician in the network under a job whose licence terms were stated before they accepted it. Audio is fingerprinted acoustically on intake and embedded metadata is read to confirm human origin. Nothing is scraped from streaming services or sheet music libraries.

What kinds of music data can you deliver?

Roman numeral and functional harmonic analysis, voice-leading annotation, score-to-MIDI and score-to-audio alignment, form and phrase labels, original compositions and arrangements with scores, MIDI, and stems, and graded comparisons of generated music with written rationales. Each request is scoped by style, instrumentation, and format, then staffed with musicians verified in that repertoire, and the pilot batch confirms the scheme before volume.

What qualifications do musicians need, and how are they paid?

Analysis jobs generally expect a theory-heavy music degree; for composition and arrangement a professional portfolio counts as much as any degree; alignment tasks need fluency with notation software and MIDI. Every job lists its rate, scope, and deadline before you accept it, there is no quota, and approved batches are credited to your account with payouts after identity and tax verification.

Can we license commissioned music and analysis exclusively?

Yes. Commissioned works, analyses, and alignment maps can be licensed to one buyer, with scope, term, and exclusivity written into the agreement before work starts. Audio ships as WebDataset or Parquet, labels and alignment maps as JSON Lines or CSV, and every delivery includes Croissant metadata and a signed receipt naming each item by identifier and hash.

Send us the piece your model is proudest of.

Tell us the styles, label layers, and volume. A data lead replies inside one business day with a staffing view, a scheme outline, and a pilot price. Musicians: the application takes ten minutes. No deck. A ranked list.

Experienced within

  • SOC 2 Type II
  • ISO 27001
  • HIPAA
  • HITRUST r2
  • ISO 27701
  • PCI DSS
  • NIST CSF 2.0
  • CMMC
  • FedRAMP
  • GDPR

Markets served.

As an enterprise AI agency, eeko systems delivers production AI systems remote-first across the United States and internationally — including these markets:

New York City, New York (NY)

Los Angeles, California (CA)

Chicago, Illinois (IL)

Houston, Texas (TX)

Phoenix, Arizona (AZ)

Philadelphia, Pennsylvania (PA)

San Antonio, Texas (TX)

San Diego, California (CA)

Dallas, Texas (TX)

San Jose, California (CA)

Austin, Texas (TX)

Jacksonville, Florida (FL)

Fort Worth, Texas (TX)

Columbus, Ohio (OH)

Charlotte, North Carolina (NC)

Indianapolis, Indiana (IN)

San Francisco, California (CA)

Seattle, Washington (WA)

Denver, Colorado (CO)

Washington, District of Columbia (DC)

Boston, Massachusetts (MA)

El Paso, Texas (TX)

Nashville, Tennessee (TN)

Detroit, Michigan (MI)

Oklahoma City, Oklahoma (OK)

Portland, Oregon (OR)

Las Vegas, Nevada (NV)

Memphis, Tennessee (TN)

Louisville, Kentucky (KY)

Baltimore, Maryland (MD)

Milwaukee, Wisconsin (WI)

Albuquerque, New Mexico (NM)

Tucson, Arizona (AZ)

Fresno, California (CA)

Sacramento, California (CA)

Kansas City, Missouri (MO)

Atlanta, Georgia (GA)

Miami, Florida (FL)

Colorado Springs, Colorado (CO)

Raleigh, North Carolina (NC)

Omaha, Nebraska (NE)

Long Beach, California (CA)

Virginia Beach, Virginia (VA)

Oakland, California (CA)

Minneapolis, Minnesota (MN)

Tulsa, Oklahoma (OK)

Arlington, Texas (TX)

New Orleans, Louisiana (LA)

Wichita, Kansas (KS)

Cleveland, Ohio (OH)

Tampa, Florida (FL)

Bakersfield, California (CA)

Aurora, Colorado (CO)

Honolulu, Hawaii (HI)

Anaheim, California (CA)

Santa Ana, California (CA)

Corpus Christi, Texas (TX)

Riverside, California (CA)

Lexington, Kentucky (KY)

St. Louis, Missouri (MO)

Stockton, California (CA)

Pittsburgh, Pennsylvania (PA)

Saint Paul, Minnesota (MN)

Cincinnati, Ohio (OH)

Greensboro, North Carolina (NC)

Anchorage, Alaska (AK)

Plano, Texas (TX)

Lincoln, Nebraska (NE)

Orlando, Florida (FL)

Irvine, California (CA)

Newark, New Jersey (NJ)

Toledo, Ohio (OH)

Durham, North Carolina (NC)

Chula Vista, California (CA)

Fort Wayne, Indiana (IN)

Jersey City, New Jersey (NJ)

St. Petersburg, Florida (FL)

Laredo, Texas (TX)

Madison, Wisconsin (WI)

Chandler, Arizona (AZ)

Buffalo, New York (NY)

Lubbock, Texas (TX)

Scottsdale, Arizona (AZ)

Reno, Nevada (NV)

Glendale, Arizona (AZ)

Gilbert, Arizona (AZ)

Winston-Salem, North Carolina (NC)

North Las Vegas, Nevada (NV)

Norfolk, Virginia (VA)

Chesapeake, Virginia (VA)

Fremont, California (CA)

Garland, Texas (TX)

Richmond, Virginia (VA)

Baton Rouge, Louisiana (LA)

Boise, Idaho (ID)

San Bernardino, California (CA)

Spokane, Washington (WA)

Des Moines, Iowa (IA)

Modesto, California (CA)

Birmingham, Alabama (AL)

Tacoma, Washington (WA)

Fontana, California (CA)

Oxnard, California (CA)

Fayetteville, North Carolina (NC)

Huntsville, Alabama (AL)

Moreno Valley, California (CA)

Rochester, New York (NY)

Glendale, California (CA)

Yonkers, New York (NY)

Augusta, Georgia (GA)

Amarillo, Texas (TX)

Little Rock, Arkansas (AR)

Akron, Ohio (OH)

Shreveport, Louisiana (LA)

Grand Rapids, Michigan (MI)

Mobile, Alabama (AL)

Salt Lake City, Utah (UT)

Huntsville, Texas (TX)

Tallahassee, Florida (FL)

Overland Park, Kansas (KS)

Knoxville, Tennessee (TN)

Worcester, Massachusetts (MA)

Brownsville, Texas (TX)

New Port Richey, Florida (FL)

Jackson, Mississippi (MS)

Providence, Rhode Island (RI)

Fort Lauderdale, Florida (FL)

Sioux Falls, South Dakota (SD)

Tempe, Arizona (AZ)

Cape Coral, Florida (FL)

Springfield, Missouri (MO)

Pembroke Pines, Florida (FL)

Eugene, Oregon (OR)

Peoria, Arizona (AZ)

Corona, California (CA)

Lancaster, California (CA)

Rockford, Illinois (IL)

Salinas, California (CA)

Palmdale, California (CA)

Springfield, Massachusetts (MA)

Charleston, South Carolina (SC)

Duluth, Minnesota (MN)

London, England (ENG)

Dublin, Ireland (IRE)