Traktomizer Online Help – Quick Reference
Traktomizer Keyboard Shortcuts
key [1] => View Project Pallet
key [2] => View Song Analysis Charts
key [3] => View OpenGL Charts
key [4] => View Social Media Metrics
key [5] => View Genre Charts
key [6] => View Summary Charts
key [7] => View Progress Viewport
key [8] => View Media Player
key [9] => View Loudness Charts
key [T] => View My Songs Database
key [B] => View Benchmark Songs Database
key [D] => View Dashboard
key [C] => View PNG Decompositions Gallery
key [U] => View Custom Charts
key [W] => Reset Views to Default
key [F] => Toggle Fullscreen
Ctrl+[A] => Reprocess OpenGl &Audio | reproduces all OpenGL and PNG decomposition visualizations, useful when your audio-file has iterated and you need visualizations without re-analyzing or benchmarking audio properties.
Ctrl+[L] => Open &Last Audio file | same as Ctrl+A except you won’t be prompted by a file-requester, the previous file will be re-rendered.
Ctrl+[P] => View Preferences | Edit your artist profile, register and activate/reactivate your software.
Ctrl+[Q] => Quit the application
Audio Property Descriptions
acousticness
float: confidence the track is “acoustic” (0.0 to 1.0)
danceability
float: relative danceability (0.0 to 1.0)
duration
float: length of track in seconds
energy
float: relative energy (0.0 to 1.0)
key
int: between 0 (key of C) and 11 (key of B flat) inclusive
liveness
float: confidence the track is “live” (0.0 to 1.0)
loudness
float: overall loudness in decibels (dB)
mode
int: 0 (major) or 1 (minor)
speechiness
float: likelihood the track contains speech (0.0 to 1.0)
tempo
float: overall BPM (beats per minute)
time_signature
beats per measure (e.g. 3, 4, 5, 7)
valence
float: a range from negative to positive emotional content (0.0 to 1.0)
RMS
Root mean square of all the elements, flattened out
dB(level)
Return a level in decibels
Spectral Flatness (spectrum)
The spectral flatness is calculated by dividing the geometric mean of the power spectrum by the arithmetic mean of the power spectrum
Measurements that include DC component:
DC_offset = mean(signal)
bitrate = DC_offset = mean(signal)
Maximum/minimum sample value
Estimate of true bit rate
Measurements that don’t include DC
signal_level
peak_level
crest_factor
A-weighting filter to the signal
weighted = A_weight(signal, sample_rate)
weighted_level = rms_flat(weighted)
Loudness Comparisons
Chart overlay of dB Values for two songs at a time.
Detailed descriptions about audio properties are available in the User Manual as well as Echonest Analyzer Documentation (http://developer.echonest.com/docs/v4/_static/AnalyzeDocumentation.pdf) and EchoNest Acoustic Attributes Overview (http://developer.echonest.com/acoustic-attributes.html)
The following attributes are available from the EchoNest Remix API and used by :
analysis_channels
int: the number of audio channels used during analysis
analysis_sample_rate
int: the sample rate used during analysis
bars
list of dicts: timing of each measure
beats
list of dicts: timing of each beat
codestring
ENMFP code string
code_version
version of ENMFP code generator
decoder
audio decoder used by the analysis (e.g. ffmpeg)
echoprintstring
fingerprint string using Echoprint (http://echoprint.me)
echoprint_version
version of Echoprint code generator
end_of_fade_in
float: time in seconds track where fade-in ends
key_confidence
float: confidence that key detection was accurate
meta
dict: other track metainfo (bitrate, album, genre, etc.)
mode_confidence
float: confidence that mode detection was accurate
num_samples
int: total samples in the decoded track
sample_md5
str: 32-character checksum of the decoded audio file
samplerate
the audio sample rate detected in the file
sections
list of dicts: larger sections of song (chorus, bridge, solo, etc.)
segments
list of dicts: timing, pitch, loudness and timbre for each segment
start_of_fade_out
float: time in seconds where fade out begins
synchstring
string providing synchronization points throughout the track
synch_version
version of the synch string algorithm
tatums
list of dicts: the smallest metrical unit (subdivision of a beat)
tempo_confidence
float: confidence that tempo detection was accurate
time_signature_confidence
float: confidence that time_signature detection was accurate
Each bar, beat, section, segment and tatum has a start time, a duration, and a confidence,
in addition to whatever other data is given.