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A C++ Library for Audio Analysis
audio
music
gist
c-plus-plus
audio-analysis
music-information-retrieval
fft
mfcc
mir
spectral-analysis
pitch-tracking
onset-detection
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Updated
Sep 18, 2021 - C++
Tutorial covering Open Source tools for Source Separation.
music
open-source
tutorial
music-information-retrieval
mir
source-separation
ismir
music-separation
ismir2020
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Updated
Nov 11, 2021 - Jupyter Notebook
magdalenafuentes
commented
Mar 21, 2021
Otherwise the first track of the index is loaded. Contributors right now realize this because they submit their PR and it fails.
An small explanation should be added to the docs.
.NET DSP library with a lot of audio processing functions
audio
sound-effects
dsp
fda
wav
feature-extraction
noise
signal
lpc
resampling
filtering
mfcc
pitch
mir
adaptive-filtering
psychoacoustics
wavelets
sound-synthesis
time-stretch
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Updated
Oct 7, 2021 - C#
Fast and simple music and audio analysis using RNN in Python 🕵️♀️ 🥁
audio
python
music
data
machine-learning
analysis
audio-features
pypi
ml
pip
feature-extraction
music-information-retrieval
sample-rate
rnn
beats
tempo
mir
beat-detection
-
Updated
Jul 13, 2018 - Python
[REPO] Music Genre classification on GTZAN dataset using CNNs
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Updated
Aug 25, 2021 - Python
Contactless EMV credit card reader
credit-card
payments
nfc
visa
pan
mir
emv
nfc-card-reader
mastercard
pn532
nfc-reader
contactless
nfc-cards
nfc-scanner
nfcmillionaire
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Updated
Oct 22, 2019 - C++
SEGAN pytorch implementation https://arxiv.org/abs/1703.09452
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Updated
Mar 11, 2019 - Python
Package for automatic beat-mixing of music files in Python 🐻 🎚
audio
python
music
analysis
audio-features
ml
audio-analysis
pip
feature-extraction
music-information-retrieval
beats
algorithm-library
dj
mir
audio-processing
beat-detection
mixing
audioowl
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Updated
Apr 26, 2018 - Python
Music Synthesis with Python talk, originally given at PyGotham 2017.
python
music
conference
interactive
csound
audio-analysis
supercollider
talk
music-information-retrieval
synthesis
lecture
mir
librosa
pyo
music-synthesis
-
Updated
Nov 20, 2017 - Jupyter Notebook
Supplementary material for IJCNN paper "Musical Artist Classification with Convolutoinal Recurrent Neural Networks"
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Updated
Aug 25, 2021 - Python
Audio degradation toolbox in python, with a command-line tool. It is useful to apply controlled degradations to audio: e.g. data augmentation, evaluation in noisy conditions, etc.
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Updated
Feb 1, 2021 - Python
Statically detect double-lock & conflicting-lock bugs on MIR
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Updated
Apr 9, 2021 - Rust
Source code for "MusCaps: Generating Captions for Music Audio" (IJCNN 2021)
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Updated
May 20, 2021 - Jupyter Notebook
Open source library that allows you to efficiently compute audio features.
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Updated
Oct 13, 2020 - Java
A Puredata real-time music analysis patch using OSC communication.
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Updated
Jun 15, 2017 - Pure Data
Evaluation metrics for machine-composed symbolic music. Paper: "The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI-Composed Music through Quantitative Measures", ISMIR 2020
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Updated
Oct 29, 2020 - Python
Field observation quick analysis toolkit (kw: field observation, air polltion, time series summary, time series resampling, average variation, ozone formation potential (OFP), MIR, tuv).
time-series
air-quality
atmospheric-modelling
air-pollution
atmospheric-science
mir
air-quality-data
time-series-analysis
ofp
tuv
atmospheric-chemistry
air-quality-measurements
analysis-toolkit
photolysis-rate-coefficients
field-observation
daily-maximum-8-hour-ozone
ozone-formation-potential
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Updated
Nov 18, 2021 - R
AudioGuide is a standalone program for concatenative sound synthesis written in python. Interacting with the program is done via textfiles written in a simple syntax. AudioGuide renders concatenations automatically using csound, but also includes support for Max, Logic, Reaper, Pro Tools, music notation via bach, and json files.
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Updated
Jul 14, 2021 - Python
Neural network to classify certain styles of Electronic music
neural-network
tensorflow
music-information-retrieval
classification
electronic-music
mir
keras-models
audio-processing
-
Updated
Apr 4, 2019 - Jupyter Notebook
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Is your feature request related to a problem? Please describe.
Using the CLI to output parameters, those audio features who are multidimensional like
amplitudeSpectrumandmfccwill not get corresponding label names in the first row of the generated csv-file. This makes it complicated to import using csv-importers like pandas in Python.It's also unclear which bin each column represents.