Niko Chord Progression Dataset Dataset

Introduction

The Niko Chord Progression Dataset is used in AccoMontage2. It contains 5k+ chord progression pieces, labeled with styles. There are four styles in total: Pop Standard, Pop Complex, Dark and R&B. Some progressions have an 'Unknown' style. Some statistics are provided below.

| | Mean | Variance | | -------------------------- | ----- | -------- | | Note Pitch | 57 | 167.70 | | Note Velocity | 79.05 | 457.89 | | Note Duration (in seconds) | 1.38 | 1.62 |

Data Formats

You can access the Niko Chord Progression Dataset in two formats: MIDI format and the quantized note matrix format.

MIDI (dataset.zip)

Each chord progression piece is stored as a single MIDI file.

Quantized Note Matrix (dataset.pkl)

A python dictionary with format like the following. nmatis an 2-d matrix, each row represent a quantized note: [start, end, pitch, velocity]. <u>Each note is quantized at the eighth note level. eg., start=2 means the note begins at the third eighth note.</u> root is also an 2-d matrix. It labels the roots of the chords using an eighth note sample rate. Each row of the root represents a bar. Each element is an integer ranged from 0 (C note) to 11 (B note).

{'piece name': 
 	{'nmat': [[0, 3, 60, 60], ...],    # 2-d matrix: note matrix
     'root': [[0,0,0,0,0,0,0,0], ...], # 2-d matrix: root label
     'style': 'some style',            # pop_standard, pop_complex, dark, r&b, unknown
     'mode': 'some mode',              # M, m
     'tonic': 'some tonic'			   # C, Db, ... B
    }, 
 ...
}

# load the dataset using pickle
import pickle
with open('dataset_path_and_name.pkl', 'rb') as file:
    dataset = pickle.load(file)

Niko Chord Progression Dataset

Introduction

Data Formats

MIDI (dataset.zip)

Quantized Note Matrix (dataset.pkl)

Supplementary description

Original Dataset

Style Mapping

Cite

License

AccoMontage2: A Complete Harmonization and Accompaniment Arrangement System

MAESTRO

JSB Chorales

MusicNet