Audio Analysis V6 Classifier
The Cyanite API exposes a variety of classifiers for your music.
BPM#
The BPM classifier provides you the BPM of the track.
Key#
The Key classifier provides you with the predicted key.
Mood#
The mood multi-label classifier provides the following labels:
aggressive, calm, chilled, dark, energetic, epic, happy, romantic, sad, scary, sexy, ethereal, uplifting
Each label has a score ranging from 0-1, where 0 (0%) indicates that the track is unlikely to represent a given mood and 1 (100%) indicates a high probability that the track represents a given mood.
Since the mood of a track might not always be properly described by a single tag, the mood classifier is able to predict multiple moods for a given song instead of only one.
A track could be classified with dark (Score: 0.9), while also being classified with aggressive (Score: 0.8).
The mood can be retrieved both averaged over the whole track and segment-wise over time with 15s temporal resolution.
In addition to the score, the API also exposes a list that includes the most likely moods, or the term ambiguous in case of none of the audio not reflecting any of our mood tags properly.
Genre#
The genre multi-label classifier provides the following labels:
ambient, blues, classical, country, electronicDance, folk, indieAlternative, jazz, latin, metal, pop, punk, rapHipHop, reggae, rnb, rock, singerSongwriter
Each label has a score ranging from 0-1 where 0 (0%) indicates that the track is unlikely to represent a given genre and 1 (100%) indicates a high probability that track represents a given genre.
Since music could break genre borders the genre classifier can predict multiple genres for a given song instead of only predicting one genre.
A track could be classified with rapHipHop (Score: 0.9) but also reggae (Score: 0.8).
The genre can be retrieved both averaged over the whole track and segment-wise over time with 15s temporal resolution. In addition to the score, the API also exposes a list that includes the most likely genres.
Sub-genre#
For some tracks an additional sub-genre can be predicted. Possible sub-genres include:
bluesRock, folkRock, hardRock, indieAlternative, psychedelicProgressiveRock, punk, rockAndRoll, popSoftRock, abstractIDMLeftfield, breakbeatDnB, deepHouse, electro, house, minimal, synthPop, techHouse, techno, trance, contemporaryRnB, gangsta, jazzyHipHop, popRap, trap, blackMetal, deathMetal, doomMetal, heavyMetal, metalcore, nuMetal, disco, funk, gospel, neoSoul, soul, bigBandSwing, bebop, contemporaryJazz, easyListening, fusion, latinJazz, smoothJazz, country, folk
Each label has a score ranging from 0-1 where 0 (0%) indicates that the track is unlikely to represent a given sub-genre and 1 (100%) indicates a high probability that track represents a given sub-genre.
The sub-genre can be retrieved both averaged over the whole track and segment-wise over time with 15s temporal resolution. In addition to the score, the API also exposes a list that includes the most likely sub-genres.
caution
Some tracks don't have any sub-genre. In this case the sub-genre tags is an empty array and averaged segments values are unavailable.
Voice#
The voice classifier categorizes the audio as female or male singing voice or instrumental (non-vocal).
Each label has a score ranging from 0-1 where 0 (0%) indicates that the track is unlikely to have the given voice elements and 1 (100%) indicates a high probability that track contains the given voice elements.
The voice classifier results can be retrieved both averaged over the whole track and segment-wise over time with 15s temporal resolution.
Voice Presence Profile#
This label describes the amount of singing voice throughout the full duration of the track and may be none, low, medium or high.
Predominant Voice Gender#
This label indicates if the predominant singing voice holds more likely female or male characteristics. It may be none if no singing voice is detected.
Instruments#
The instrument classifier predicts the presence of the following instruments: percussion, synth, piano, acousticGuitar, electricGuitar, strings, bass, bassGuitar and brassWoodwinds.
It is possible to retrieve the presence of each instrument for each track segment, a list of the dominant instruments and a taxonomy that describes the presence of each instrument over the complete track.
The segment instrument score reaches from 0-1 where 0 (0%) indicates that the segment is unlikely to contain a given instrument and 1 (100%) indicates a high probability that the track segment contains a given instrument.
The taxonomy absent, partially, frequently and throughout describe the presence of each instrument
| Taxonomy | Description |
|---|---|
absent | Instrument has not been detected |
throughout | Instrument is detected throughout the full duration of the track |
frequently | Instrument is detected in major parts of the track |
partially | Instrument is detected in minor parts of the track. |
AudioAnalysisV6Segments.instrumentsAudioAnalysisV6Result.instrumentPresenceAudioAnalysisV6InstrumentPresenceAudioAnalysisV6Result.instrumentTagsAudioAnalysisV6InstrumentTagsAudioAnalysisV6Result.instruments(deprecated)
Valence / Arousal#
The valence / arousal regression model predicts the degree of valence or arousal of a track.
Each label has a score ranging from -1 to 1 where -1 indicates the lowest degree (negative valence, negative arousal) and 1 indicates the highest degree (positive valence, positive arousal).
The voice valence / arousal results can be retrieved both averaged over the whole track and segment-wise over time with 15s temporal resolution.
Energy Level#
The Energy Level is a label for the intensity of an analysed track which can be either variable, medium, high, low.
A low Energy Level indicates a calm overall appearance of a track while a high one stands for more strong and powerful characteristics.
A track with a variable energy level will hold steady changes in its intensity profile.
Energy Dynamics#
Energy Dynamics describes the progression of the Energy Level throughout the duration of the music piece, where the value low represents a stable trend and high depicts a strong variance between low and high energy levels.
The high value indicates variable energy level (see above).
Musical Era#
The musical era classifier describes the era the audio was likely produced in, or which the sound of production suggests.
Keywords (Experimental)#
Experimental taxonomy that can be associated with the audio. The data is experimental and expected to change. The access must be requested from the cyanite sales team.
Example keywords:
uplifting, edm, friendly, motivating, pleasant, happy, energetic, joy, bliss, gladness, auspicious, pleasure, forceful, determined, confident, positive, optimistic, agile, animated, journey, party, driving, kicking, impelling, upbeat,