10. Audio mosaicing
An example of basic audio mosaicking in bellplay~, where a target audio file is reconstructed using segments drawn from a small audio corpus.
An example of basic audio mosaicking in bellplay~, where a target audio file is reconstructed using segments drawn from a small audio corpus.
This example demonstrates how to align the envelopes of different audio samples based on their peak amplitude times.
This example automatically generates a custom keymap given a list of audio file paths:
This tutorial demonstrates how to use a multi-layer perceptron (MLP) neural network
One of the core features in bellplay~ is our ability to analyze buffers to extract relevant information.
When analyzing buffers, we can specify the output format for many of the available audio descriptors.
This tutorial provides an additional example for using buffer analysis features for audio processing.
Some basic familiarity with SQLite3 is expected to fully understand this tutorial.
In bellplay~, computation-heavy operations such as building large corpora, analyzing lots of audio data, and more, can be take a very long time, thus making it more tedious to experiment with our scripts every time we run them.
This tutorial shows how to build k-dimensional trees to efficiently perform feature-based search on buffers.
This tutorial demonstrates how to perform rudimentary source separation
A basic example of temporal quantization, where transient-based segments are temporally shifted to align with a rhythmic grid.
barkbands
bfcc
chordsdetection
dissonance
effectiveduration
energy
energyband
envmaxtime
envmintime
flux
inharmonicity
larm
logattack
maxmagfreq
mfcc
onsetdetection
onsets
pitchmelodia
pitchyin
rhythm
rolloff
spectralcentroid
spectralflatness
spectralkurtosis
spectralskewness
spectralspread
spectralvariance
spectrum
strongdecay
strongpeak
temporalcentroid
temporalflatness
temporalkurtosis
temporalskewness
temporalspread
temporalvariance
tonalkey
zerocrossingrate