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Track and Recording Metadata

CustomerName_Recording_YYYYMMDD.json​

id
required
number

Dataset: Basic
ID of the recording

title
required
string

Dataset: Basic
Title of the recording

subtitle
string

Dataset: Basic
Subtitle of the recording

duration
string

Dataset: Basic
Duration of the recording, with format “HH:MM:SS”

isrc
string

Dataset: Basic
ISRC of the recording

hit
number

Dataset: Basic
Rating if the recording has been in the charts

editors_pick
number

Dataset: Basic
Rating if the recording is recommended by the Music Story editorial team

object

Dataset: Basic
Object containing the IDs of the recording in external databases and platforms

Array of objects

Dataset: Basic
Array containing the recording translated names

related_isrcs
Array of strings
Deprecated

Dataset: Basic
Array of related isrcs

id_genre
number

Dataset: Basic
ID of the recording genre

Array of objects

Dataset: Basic
Object containing the artists information

object

Dataset: Lyrics
Object containing the lyrics information

object

Dataset: Explicit
Object containing the explicit information from label or lyrics

Array of objects

Dataset: Basic
Array of tracks to the recording

{
  • "id": 49846,
  • "title": "Thunderstruck",
  • "subtitle": null,
  • "duration": "00:06:34",
  • "isrc": "AUAP09200021",
  • "hit": null,
  • "editors_pick": null,
  • "externals": {
    },
  • "translated": [
    ],
  • "related_isrcs": null,
  • "id_genre": 143,
  • "artists": [
    ],
  • "lyric": {
    },
  • "explicit": {
    },
  • "tracks": [
    ]
}

CustomerName_Recording_Charts_YYYYMMDD.json​

id_recording
required
number

Dataset: Chart
ID of the recording

Array of objects

Dataset: Chart
Array containing all charts of the recording

{
  • "id_recording": 52,
  • "charts": [
    ]
}

CustomerName_Recording_Audio_Descriptions_YYYYMMDD.json​

id_recording
required
number

Dataset: Audio
ID of the recording

absolute_loudness
number

Dataset: Audio
Related to the perceived intensity of the audio signal

arousal
number

Dataset: Audio
Perceptual measure related to intensity, energy and activity. High value usually corresponds to high energy track (hard rock, metal). Low value is given to calm tracks (slow, ballad).

articulation
number

Dataset: Audio
Indicates whether a track contains sounds with staccato articulation. High value corresponds to tracks with a lot of fast notes, arpeggiators for example. Low value is related to relaxed tracks with long sustained notes, electronic textures for example.

binary
number

Dataset: Audio
Rhythmic property of the track. Do listeners perceive the rhythm of the track binary or not (ternary for example) The higher the value, the higher the probability for the track to be binary.

bpm
number

Dataset: Audio
BPM of the recording

brightness
number

Dataset: Audio
The impression of brightness of a sound/music.

centroid
number

Dataset: Audio
Indicates where the center of mass of the spectrum is located.

chroma01
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma02
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma03
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma04
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma05
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma06
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma08
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma09
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma10
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma11
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

chroma12
number

Dataset: Audio
The chroma coefficients are the energy of the spectrum projected onto 12 bins representing the 12 distinct semitones of the musical octave.

complexity
number

Dataset: Audio
Rhythmic complexity of the track, i.e. the difficulty to repeat by tapping or to find the meter. The higher the value, the more complex the perceived rhythm is.

complexity_chroma
number

Dataset: Audio
Related to the noisiness of the chroma representation. A high value indicates a track with complex tonal properties, while a low value indicates simple tonal properties.

danceability
number

Dataset: Audio
Indicates if a track is likely to be considered for dancing (perception of tempo and rhythm, stability and regularity). High value corresponds to more danceable tracks. Low value is related to tracks without any perceptual rhythm.

dissonance
number

Dataset: Audio
Indicates how dissonant is a track. High value corresponds to tracks without clear harmony, noisy timbre for example, or with very complex harmonies (dissonant intervals such as tritones, seconds, etc). Low value corresponds to tracks with simple harmony, clear melody, consonant harmonies (simple piano melodies for example).

electric_acoustic
number

Dataset: Audio
Indicates whether the track contains acoustic content. High value corresponds to acoustic tracks (acoustic guitar/piano, voice, classical music). Low value indicates tracks with electric content (electronic, distortion, audio effects).

event_density
number

Dataset: Audio
Number of percussive events per time unit, i.e. the speed of the track. A track with a high event density contains fast musical events (notes or percussion) A track with low event density is generally made of slow/sustained notes.

flatness
number

Dataset: Audio
Provides a way to quantify how tone-like a sound is, as opposed to being noise-like. Tonal signals tend to have a small value, while noisy signals tend to have a high value.

intensity
number

Dataset: Audio
Related to the intensity of the audio signal.

loudness
number

Dataset: Audio
Related to the normalized perceived intensity of the audio signal.

loudness_range
number

Dataset: Audio
Related to the dynamic range of the audio signal.

melodicity
number

Dataset: Audio
Indicates whether a track contains or not a clearly audible melody. High value corresponds to pleasant, harmonic tracks, to which you feel like singing along.

Low value is more related to noises, soundscapes or tracks with complex harmonies or melodies (classical, jazz, etc).

mfcc01
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc02
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc03
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc04
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc05
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc06
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc07
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc08
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc09
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc10
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc11
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc12
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

mfcc13
number

Dataset: Audio
The MFCC represents the shape of the spectrum with very few coefficients.

Array of objects

Dataset: Audio
Array of object contains all moods of the recording

music_speech
number

Dataset: Audio
Indicates speech content in a track. High value is related to the presence of spoken words (interview, audio book, poetry, commentary). Low value probably corresponds to music, eventually with vocals (singing tracks), but without speech parts.

pulse_clarity
number

Dataset: Audio
Perception of tempo. If the tempo is clear and very stable, the value is high. Low value indicates a track without rhythm or with unstable tempo.

rhythmic_stability
number

Dataset: Audio
Perception of tempo. If the tempo is clear and very stable, the value is high. Low value indicates a track without rhythm or with unstable tempo.

roll_off
number

Dataset: Audio
Defined as the frequency under which 85% of the total energy of the spectrum is contained. It is correlated somehow to the harmonic/noise cutting frequency.

spread
number

Dataset: Audio
Defined as the spread of the spectrum around its mean value.

studio_live
number

Dataset: Audio
Indicates the probability that the track has been performed live. High value corresponds to live tracks. Low value is more probably related to studio recordings.

themes
Array of strings

Dataset: Audio
String table contains all themes of the recording

timbres
Array of strings

Dataset: Audio
String table contains all timbres of the recording

valence
number

Dataset: Audio
Perceptual measure of mood, related to positive or negative feelings, for example joy/sadness. High value corresponds to track with positive feelings. Low value refers to sad tracks.

vocal_instrumental
number

Dataset: Audio
Indicates whether a track contains or not vocals. High value indicates that the track probably contains no vocal sounds (instrumental) Low value probably corresponds to track with vocal content (singing words, rap, slam or speech for example).

zero_cross_rate
number

Dataset: Audio
Number of times the signal value crosses the zero axe. Noisy sounds tend to have a high value, whereas periodic sounds tend to have a small value.

{
  • "id_recording": 143,
  • "absolute_loudness": -17.017862,
  • "arousal": 0.37747,
  • "articulation": 0.35062,
  • "binary": 0.868598,
  • "bpm": 146,
  • "brightness": 0.158628,
  • "centroid": 2778.38969,
  • "chroma01": 8658,
  • "chroma02": 3481,
  • "chroma03": 10443,
  • "chroma04": 3288,
  • "chroma05": 2751,
  • "chroma06": 9074,
  • "chroma08": 6639,
  • "chroma09": 2315,
  • "chroma10": 10069,
  • "chroma11": 6586,
  • "chroma12": 1820,
  • "complexity": 0.535129,
  • "complexity_chroma": 0.272727,
  • "danceability": 0.30291,
  • "dissonance": 0.41116,
  • "electric_acoustic": 0.29396,
  • "event_density": 0.054121,
  • "flatness": 0.178921,
  • "intensity": 0.112553,
  • "loudness": -17.55953,
  • "loudness_range": 13.602145,
  • "melodicity": 0.6386,
  • "mfcc01": -9.155933,
  • "mfcc02": 3.140339,
  • "mfcc03": -0.973053,
  • "mfcc04": 0.531556,
  • "mfcc05": -0.206241,
  • "mfcc06": -0.383538,
  • "mfcc07": -0.100084,
  • "mfcc08": -0.1996,
  • "mfcc09": -0.526851,
  • "mfcc10": -0.162105,
  • "mfcc11": -0.491767,
  • "mfcc12": -0.176531,
  • "mfcc13": -0.180867,
  • "moods": [
    ],
  • "music_speech": 0.06266,
  • "pulse_clarity": 0.109689,
  • "rhythmic_stability": 0.42617,
  • "roll_off": 1507.72772,
  • "spread": 3330.485295,
  • "studio_live": 0.19556,
  • "themes": [
    ],
  • "timbres": [
    ],
  • "valence": 0.12499,
  • "vocal_instrumental": 0.07184,
  • "zero_cross_rate": 0.057647
}

CustomerName_Recording_Lyricfind_YYYYMMDD.json​

customername_id
required
number

Dataset: Lyrics
ID of the recording

lyricfind_id
required
number

Dataset: Lyrics
Lyricfind ID of the recording

is_sync
required
boolean

Dataset: Lyrics
Whether the recording is synced with lyricfind

type_match
required
string
Enum: "ARTIST_TITLE" "ISRC"

Dataset: Lyrics
Type of match with lyricfind

{
  • "customername_id": 123,
  • "lyricfind_id": "002-19525736",
  • "is_sync": true,
  • "type_match": "ARTIST_TITLE"
}

CustomerName_Recording_Credits_YYYYMMDD.json​

All possible values are available in the appendix > credit section.

id_recording
required
number

Dataset: Credit
ID of the recording

Array of objects

Dataset: Credit
Table of object containing the credits information

{
  • "id_recording": 696211,
  • "data": [
    ]
}

CustomerName_Recording_Popularity_YYYYMMDD.json​

id_recording
required
number

Dataset: Popularity
ID of the recording

type
required
string

Dataset: Popularity
The most representative type of popularity for a recording

peak
required
number

Dataset: Popularity
Most representative date in years

object

Dataset: Popularity
Object contains global info of popularity of the recording

object

Dataset: Popularity
Object contains catalog info of popularity of the recording

object

Dataset: Popularity
Object contains current info of popularity of the recording

{
  • "id_recording": 143,
  • "type": "gold",
  • "peak": 2020,
  • "global": {
    },
  • "catalog": {
    },
  • "current": {
    }
}

CustomerName_Matching_Recording_YYYYMMDD.json​

id_customername
required
any

Dataset: Matching
ID of the recording in the Customer catalog

id_musicstory
required
number

Dataset: Matching
ID of the corresponding recording in the Music Story catalog

{
  • "id_customername": null,
  • "id_musicstory": 0
}

CustomerName_Deleted_Recording_YYYYMMDD.json​

id
required
number

Dataset: Basic
ID of the deleted recording

{
  • "id": 0
}

CustomerName_Deleted_Matching_Recording_YYYYMMDD.json​

id_customername
required
any

Dataset: Matching
ID of the recording in the Customer catalog

id_musicstory
required
number

Dataset: Matching
ID of the corresponding recording in the Music Story catalog

{
  • "id_customername": null,
  • "id_musicstory": 0
}