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This page lists plugins made by research groups and developers around the world. It is generated automatically from RDF descriptions published by the plugin authors. /good-free-vst-plugins-for-fl-studio.html.

▶ How to Install — For installation instructions see the bottom of this page.

Easy Sound Space Perception is a small and lightweight audio visualization tool, which currently provides spectrometer and goniometer views. The main advantage of this tool is that it can render information about up to four stereo pairs at the same time onto the same surface using different colors (see. VST, AudioUnits? Sonic Visualiser cannot support VST plugins directly because Steinberg's VST license is incompatible with Sonic Visualiser's GPL license. Windows and OS/X users can get limited support using the Audacity VST Enabler, and Linux users can try dssi-vst. Mac: LCAST comes in three versions on the Mac: an AAX plug-in for Pro Tools (10.3.7+), an Audio Unit and a VST 2.4 plug-in. All plug-ins are 32/64-bit universal binaries. Windows: LCAST is available as a 32/64-bit AAX plug-in for Pro Tools (10.3.7+) and a VST 2.4 plug-in on Windows. Get the 200 best free VST plugins ever made. From synth VSTs and drum VSTs to VST effects, this huge list has only the best of the best plugins.

▶ Vamp Plugin Pack — Some of these plugins are also available in the Vamp Plugin Pack, a convenient bundle installer.

ClipShifter is a wave shaping audio Mastering VST plugin that functions like a clipping-style limiter, and can be used at all mixing stages, from distorting basses and drums to maximizing mix buses and warming up mixes.

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Currently featured

• MELODIA - Melody Extraction
  • Visualisation
    Provides visualisations of the intermediate steps calculated by the melody extraction algorithm implemented in the MELODIA - Melody Extraction plug-in. For further details please read:
    J. Salamon and E. Gomez, 'Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics', IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, 2012.
    We would highly appreciate the above reference being cited in publications of work in which this plug-in was used.
  • Pitch
    Estimates the melody pitch in polyphonic music (also good for homophonic and monophonic music). Segments without melody are indicated by zero or negative values. For further details please read:
    J. Salamon and E. Gomez, 'Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics', IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, 2012.
    We would highly appreciate the above reference being cited in publications of work in which this plug-in was used.

All plugins

• BBC Vamp Plugins
  Included in Vamp Plugin Pack

  A collection of audio feature extraction algorithms from BBC Research and Development.

  • Energy
    Calculates the RMS energy and low energy ratio of a signal.
  • Low Level Features
    Calculates the intensity of a signal and the intensity ratio for a number of sub-bands.
  • Low Level Features
  • Rhythm
    Calculates rhythmic features of a signal, including onsets and tempo.
  • Low Level Features
    Calculates the peak and valleys of the spectral contrast feature.
  • Low Level Features
  • Speech/Music segmenter
    Calculates boundaries between speech and music.
• BeatRoot
  Included in Vamp Plugin Pack

  A plugin implementation of the BeatRoot beat tracking system.

  • BeatRoot Beat Tracker
    Identify beat locations in music.
• Cepstral Pitch Tracker
  Included in Vamp Plugin Pack

  A straightforward cepstral pitch- and note-tracker Vamp plugin, probably most suited to tracking singing pitch.

  • Cepstral Pitch Tracker
    Estimate f0 of monophonic material using a cepstrum method.
• Chordino and NNLS Chroma
  Included in Vamp Plugin Pack

  Harmony and chord extraction plugins by Matthias Mauch at C4DM.

  • Chordino
    Chordino provides a simple chord transcription based on NNLS Chroma (as in the NNLS Chroma plugin). Chord profiles given by the user in the file chord.dict are used to calculate frame-wise chord similarities. Two simple (non-state-of-the-art!) algorithms are available that smooth these to provide a chord transcription: a simple chord change method, and a standard HMM/Viterbi approach.
  • Visualisation
    This plugin provides a number of features derived from a DFT-based log-frequency amplitude spectrum: some variants of the log-frequency spectrum, including a semitone spectrum derived from approximate transcription using the NNLS algorithm; and based on this semitone spectrum, different chroma features.
  • Key and Tonality
    The tuning plugin can estimate the local and global tuning of piece. The same tuning method is used for the NNLS Chroma and Chordino plugins.
• Constant-Q
  Included in Vamp Plugin Pack

  A plugin implementing the Constant-Q transform of a time-domain signal.

  • Chromagram
    Extract a Constant-Q spectrogram with constant ratio of centre frequency to resolution from the audio, then wrap it around into a single-octave chromagram.
  • Visualisation
    Extract a spectrogram with constant ratio of centre frequency to resolution from the input audio, specifying the frequency range in Hz.
  • Visualisation
    Extract a spectrogram with constant ratio of centre frequency to resolution from the input audio, specifying the frequency range in MIDI pitch units.
• Fan Chirp F0gram

  Audio Processing Group, Universidad de la Republica, Uruguay
  Included in Vamp Plugin Pack

  Fundamental-frequency salience visualisation based on the Fan Chirp Transform, from the Universidad de la Republica, Uruguay.

  • Fan Chirp Transform F0gram
    This plug-in produces a representation, called F0gram, which exhibits the salience of the fundamental frequency of the sound sources in the audio file. The computation of the F0gram makes use of the Fan Chirp Transform analysis. It is based on the article 'Fan chirp transform for music representation' P. Cancela, E. Lopez, M. Rocamora, International Conference on Digital Audio Effects, 13th. DAFx-10. Graz, Austria - 6-10 Sep 2010.
• HPCP - Harmonic Pitch Class Profile
  • Return the instantaneous evolution of HPCP (Harmonic Pitch Class Profile) of a signal.
• INESC Porto Beat Tracker
  Plugin from João Oliveira of the SMC Group for tempo induction and beat tracking, built on the MARSYAS framework.

  • IBT - INESC Beat Tracker
    Estimates beat locations and tempo (off-line [default] and on-line modes of operation).
• Chris Cannam and Jamie Bullock
  Included in Vamp Plugin Pack

  Low-level feature extraction plugins using Jamie Bullock's libxtract library to provide around 50 spectral and other features.

  • Autocorrelation
    Extract the autocorrelation of an audio signal.
  • Low Level Features
    Extract the average deviation of a range of values.
  • Low Level Features
  • Average Squared Difference Function
    Extract the ASDF of an audio signal.
  • Low Level Features
  • Discrete Cosine Transform
    Extract the DCT of an audio signal.
  • Low Level Features
    Extract the fundamental frequency of an audio signal.
  • Low Level Features
    Extract the fundamental frequency of an audio signal (failsafe).
  • Visualisation
  • Highest Value
    Extract the highest value from a given range.
  • Low Level Features
  • Irregularity I
    Extract the irregularity (type I) of an audio spectrum.
  • Low Level Features
    Extract the irregularity (type II) of an audio spectrum.
  • Low Level Features
  • Loudness
    Extract the loudness of an audio signal from its spectrum.
  • Low Level Features
  • Mean
    Extract the mean of a range of values.
  • Low Level Features
  • Noisiness
    Extract the noisiness of an audio spectrum.
  • Low Level Features
    Extract the number of non-zero elements in an input spectrum.
  • Low Level Features
    Extract the odd-to-even harmonic ratio of an audio spectrum.
  • Visualisation
    Extract the spectral peaks from an audio spectrum.
  • Low Level Features
  • Skewness
    Extract the skewness of a range of values.
  • Extract the average deviation of an audio spectrum.
  • Low Level Features
    Extract the spectral centroid of an audio spectrum.
  • Low Level Features
    Extract the spectral crest measure of an audio spectrum.
  • Low Level Features
    Extract the spectral flatness of an audio spectrum.
  • Low Level Features
  • Spectral Rolloff
    Extract the rolloff point of an audio spectrum.
  • Low Level Features
    Extract the spectral sharpness of an audio spectrum.
  • Low Level Features
  • Spectral Slope
    Extract the spectral slope of an audio spectrum.
  • Low Level Features
    Extract the spectral smoothness of an audio spectrum.
  • Low Level Features
  • Spectral Standard Deviation
    Extract the standard deviation of an audio spectrum.
  • Low Level Features
  • Spectrum
    Extract the spectrum of an audio signal.
  • Low Level Features
    Extract the standard deviation of a range of values.
  • Low Level Features
  • Tonality
    Extract the tonality an audio spectrum.
  • Low Level Features
    Extract the tristimulus (type I) of an audio spectrum.
  • Low Level Features
    Extract the tristimulus (type II) of an audio spectrum.
  • Low Level Features
    Extract the tristimulus (type III) of an audio spectrum.
  • Low Level Features
  • Zero Crossing Rate
    Extract the zero crossing rate of an audio signal.
• Marsyas Plugins
  Included in Vamp Plugin Pack

  Low-level feature extraction plugins containing functionality from the MARSYAS batch feature extractor.

  • Marsyas - Batch Feature Extract - Centroid
    Marsyas - Batch Feature Extract - Centroid.
  • Marsyas - Batch Feature Extract - Line Spectral Pairs
    Marsyas - Batch Feature Extract - Line Spectral Pairs.
  • Marsyas - Batch Feature Extract - Linear Prediction Cepstral Coefficients
    Marsyas - Batch Feature Extract - Linear Prediction Cepstral Coefficients.
  • Marsyas - Batch Feature Extract - Mel-Frequency Cepstral Coefficients
    Marsyas - Batch Feature Extract - Mel-Frequency Cepstral Coefficients.
  • Marsyas - Batch Feature Extract - Spectral Crest Factor
    Marsyas - Batch Feature Extract - Spectral Crest Factor.
  • Marsyas - Batch Feature Extract - Spectral Flatness Measure
    Marsyas - Batch Feature Extract - Spectral Flatness Measure.
  • Marsyas - Batch Feature Extract - Spectral Rolloff
    Marsyas - Batch Feature Extract - Spectral Rolloff.
  • Low Level Features
• MATCH Vamp Plugin
  Included in Vamp Plugin Pack

  Vamp implementation of the MATCH audio alignment algorithm from Simon Dixon. Sonic Visualiser can use this for automatic time alignment among multiple audio files.

  • Match Performance Aligner
    Calculate alignment between two performances in separate channel inputs.
• The Mazurka Project
  Spectral visualisation and feature extraction plugins from the Mazurka project.

  • Chronogram
    Chronogram.
  • Visualisation
  • Nevermore Spectrogram
    Nevermore Spectrogram.
  • Low Level Features
  • Spectral Flux
    Spectral Flux.
  • Low Level Features
• MELODIA - Melody Extraction
  • Pitch
    Estimates the melody pitch in polyphonic music (also good for homophonic and monophonic music). Segments without melody are indicated by zero or negative values. For further details please read:
    J. Salamon and E. Gomez, 'Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics', IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, 2012.
    We would highly appreciate the above reference being cited in publications of work in which this plug-in was used.
  • Visualisation
    Provides visualisations of the intermediate steps calculated by the melody extraction algorithm implemented in the MELODIA - Melody Extraction plug-in. For further details please read:
    J. Salamon and E. Gomez, 'Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics', IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, 2012.
    We would highly appreciate the above reference being cited in publications of work in which this plug-in was used.
• MIR.EDU
  An open source Vamp plug-in library written in C++ which implements a basic set of descriptors useful for teaching MIR.

  • MIR.EDU: Attack Start/End Times
    Compute the start and end times of the attack of the signal. The start and end times of the attack are computed according to Peeters (2004), see code/documentation for further details. NOTE: the accuracy of the estimation depends on the step (hop) size of the analysis, the smaller the better. The times are returned as timestamps without any values.
  • Compute the logarithm (base 10) of the duration of the attack of the signal (unit: log10(seconds)). The start and end times of the attack are computed according to Peeters (2004), see code/documentation for further details. NOTE: the accuracy of the estimation depends on the step (hop) size of the analysis, the smaller the better. The the timestamp of the returned value is the start time of the attack. For visualising the attack start and end times use the 'Attack Start/End Times' plug-in.
  • Compute the Mel Frequency Cepstral Coefficients (MFCC) for each frame. MFCCs provide a concise representation of the spectral envelope of a sound, which in turn is related to the sound's timbre. Please refer to the code in MFCC.cpp and the reference provided in MFCC.h for a detailed explanation of how MFCCs are computed.
  • Compute the root mean square of the signal for each frame.
  • Compute the spectral centroid of the signal for each frame. The unit of the values returned is Hz. If the frame is completely silent a value of 0 is returned.
  • Compute the spectral crest of the signal for each frame. The crest is defined as the ratio between the maximum spectral magnitude in the frame and the arithmetical mean of the spectral magnitudes. The minimum possible value is 1 (flat spectrum) and it increases the peakier the spectrum is. If the frame is completely silent a value of 1 (flat spectrum) is returned.
  • Compute the spectral flatness of the signal for each frame. The flatness is defined as the ratio of the geometric and arithmetical means of the spectral magnitudes. The values returned range between 0 (peaky spectrum) and 1 (flat spectrum). If the frame is completely silent a value of 1 (flat spectrum) is returned.
  • Compute the spectral flux between every two consecutive frames of the signal. The flux is defined as 1 minus the normalized correlation between successive magnitude spectra. The values returned range between 0 (no change) and 1 (maximum change). For the first frame the flux is always zero. If both frames are silent flux = 0, if only one is silent flux = 1.
  • Compute the spectral kurtosis of the signal for each frame. The kurtosis is a measure of the peakedness of a distribution. For a gaussian distribution kurtosis = 3, for a flat distribution kurtosis < 3 and for a peakier distribution kurtosis > 3.If the frame is completely silent a value of 0 is returned.
  • Compute the spectral roll-off of the signal for each frame, defined as the frequency below which 95% of the signal energy is contained. The threshold (95%) is defined as a paramtere that can be changed by the user. The unit of the values returned is Hz. If the frame is completely silent a value of 0 is returned.
  • Compute the spectral skewness of the signal for each frame. If the frame is completely silent a value of 0 is returned.
  • Compute the spectral spread of the signal for each frame. The unit of the values returned is Hz. If the frame is completely silent a value of 0 is returned.
  • Compute the temporal centroid of the entire signal, which is the centre of gravity of the energy of the signal. Energy is represented by the RMS of the signal. The termporal centroid is computed between times n1 and n2 which are the first and last times the signal RMS is above 15% of its maximum value. The temporal centroid is returned as a timestamp with no corresponding value.
  • Compute the zero crossing rate of the signal for each frame (i.e. the number of times the signal changes sign). The unit of the values returned is crossings/second.
• Chris Cannam
  Plugin that performed audio fingerprinting and lookup using the no-longer-supported MusicIP OFA library. This plugin is provided for interest only and is no longer practically useful.

  • MusicIP Audio Fingerprinter
    Calculates an audio fingerprint using the MusicIP OFA fingerprinting library.
  • Calculates an audio fingerprint using the MusicIP OFA fingerprinting library and uses it to look up a MusicDNS PUID.
• OnsetsDS plugin
  Note onset detector using Dan Stowell's OnsetsDS library.

  • OnsetsDS Onset Detector
    Detect note onsets.
• pYIN
  Included in Vamp Plugin Pack

  pYIN is a modification of the well-loved YIN algorithm for fundamental frequency (F0) estimation in monophonic audio.

  • Local Candidate PYIN
    Monophonic pitch and note tracking based on a probabilistic Yin extension.
  • Pitch
    Monophonic pitch and note tracking based on a probabilistic Yin extension.
  • Pitch
    A vamp implementation of the Yin algorithm for monophonic frequency estimation.
• Queen Mary plugin set
  Included in Vamp Plugin Pack

  Plugins from the Centre for Digital Music at Queen Mary, University of London.

  • Adaptive Spectrogram
    Produce an adaptive spectrogram by adaptive selection from spectrograms at multiple resolutions.
  • Bar and Beat Tracker
    Estimate bar and beat locations.
  • Chromagram
    Extract a series of tonal chroma vectors from the audio.
  • Constant-Q Spectrogram
    Extract a spectrogram with constant ratio of centre frequency to resolution from the input audio.
  • Discrete Wavelet Transform
    Visualisation by scalogram.
  • Key Detector
    Estimate the key of the music.
  • Mel-Frequency Cepstral Coefficients
    Calculate a series of MFCC vectors from the audio.
  • Note Onset Detector
    Estimate individual note onset positions.
  • Polyphonic Transcription
    Transcribe the input audio to estimated notes.
  • Segmenter
    Divide the track into a sequence of consistent segments.
  • Similarity
    Return a distance matrix for similarity between the input audio channels.
  • Tempo and Beat Tracker
    Estimate beat locations and tempo.
  • Tonal Change
    Detect and return the positions of harmonic changes such as chord boundaries.
• RGU Mel-Frequency Spectrum
  Requires VamPy

  A music-inspired texture representation implemented as a VamPy plugin, from Robert Gordon University in Aberdeen.

  • Vampy MFS Plugin
    MFS plugin.
• Segmentino
  Included in Vamp Plugin Pack

  Plugin for automatic music structural segmentation.

  • Segmentino
    Estimate contiguous segments pertaining to song parts such as verse and chorus.
• Silvet Note Transcription
  Included in Vamp Plugin Pack

  Silvet, or Shift-Invariant Latent Variable Transcription, is a Vamp plugin for polyphonic music transcription (from audio to note times and pitches).

  • Silvet Note Transcription
    Estimate the note onsets, pitches, and durations that make up a music recording.
• Simple Cepstrum
  Included in Vamp Plugin Pack

  A simple Vamp plugin to calculate and return cepstrum values from DFT bins. Useful as a preliminary tool for looking at cepstral data for simple pitch or envelope methods.

  • Simple Cepstrum
    Return simple cepstral data from DFT bins. This plugin is intended for casual inspection of cepstral data. It returns a lot of different sorts of data and is quite slow; it's not a good way to extract a single feature rapidly.
• Stereo Plan
  Included in Vamp Plugin Pack

  • Return a stereo plan decomposition of the audio. The returned feature grid covers the stereo plan from left-channel-only (first bin) to right-channel-only (last bin), with each value indicating what proportion of signal energy is found at that point on the plan at that moment. The input should consist of two channels containing left and right channel signals.
• Tempogram
  Included in Vamp Plugin Pack

  A Vamp plugin implementation of the tempogram and cyclic tempogram features described in Grosche, Müller, and Kurth 2010.

  • Tempogram
    Cyclic Tempogram as described by Peter Grosche and Meinard Müller.
• Tipic - Tibre-Invariant Pitch Chroma
  Included in Vamp Plugin Pack

  Pitch-chroma audio features approaching timbre invariance, after the paper 'Towards timbre-invariant audio features for harmony-based music' by Meinard Müller and Sebastian Ewert.

  • Timbre-Invariant Pitch Chroma
    Pitch and chroma features with optional DCT timbre reduction.
• Tuning Difference
  Included in Vamp Plugin Pack

  Estimate the tuning frequency of a recording, by comparing it to another recording of the same music whose tuning frequency is known.

  • Tuning Difference
    Estimate the tuning frequency of a recording, by comparing it to another recording of the same music whose tuning frequency is known.
• University of Alicante Vamp Plugins
  Included in Vamp Plugin Pack

  The UAPlugins set is a library of Vamp plugins developed in the DRIMS project to perform onset detection and polyphonic transcription. The methods used in this library were developed by Antonio Pertusa and José Manuel Iñesta.

  • Note Onset Detector
    Note onset detection using a one-semitone filterbank.
  • Notes
    Multiple fundamental frequency estimation for polyphonic music transcription.
• Vamp Aubio plugins
  Included in Vamp Plugin Pack

  The Vamp Aubio Plugins provide methods from Paul Brossier's aubio annotation library, including beat and tempo tracking, onset detection, pitch detection, note tracking, silence detector, and Mel-frequency cepstral coefficients.

  • Aubio Beat Tracker
    Estimate the musical tempo and track beat positions.
  • Low Level Features
  • Aubio Mfcc Extractor
    Extract Mel-Frequency Cepstrum Coefficients.
  • Notes
    Estimate note onset positions, pitches and durations.
  • Time → Onsets
  • Aubio Pitch Detector
    Track estimated note pitches.
  • Low Level Features
  • Aubio Spectral Descriptor
    Compute spectral description function.
• Vamp SDK Example Plugins
  Included in Vamp Plugin Pack

  A set of simple plugins as included with the Vamp developers kit. Amplitude tracker, simple percussion onset detector, tempo estimator, spectral centroid, power spectrum, and zero-crossing counter.

  • Amplitude Follower
    Track the amplitude of the audio signal.
  • Simple Fixed Tempo Estimator
    Study a short section of audio and estimate its tempo, assuming the tempo is constant.
  • Simple Percussion Onset Detector
    Detect percussive note onsets by identifying broadband energy rises.
  • Simple Power Spectrum
    Return the power spectrum of a signal.
  • Spectral Centroid
    Calculate the centroid frequency of the spectrum of the input signal.
  • Zero Crossings
    Detect and count zero crossing points.

How to Install

A Vamp plugin set consists of a single dynamic library file with .dll, .dylib, or .so extension (depending on your platform), plus optionally a category file with .cat extension and an RDF description file with .ttl or .n3 extension.

To install a plugin set, copy the plugin's library file and any supplied category or RDF files into your system or personal Vamp plugin location.

The plugin file extension and the location to copy into depend on which operating system you are using:

Spotify Visualizer Plugin

Audio Visualizer Plugin

You can alternatively set the VAMP_PATH environment variable to override the search path for for Vamp plugins. VAMP_PATH should contain a semicolon-separated (on Windows) or colon-separated (macOS, Linux) list of directory locations. If it is set, it will completely override the standard locations listed above. (N.B. When using 32-bit plugins on 64-bit Windows, some hosts will check for the VAMP_PATH_32 environment variable instead of VAMP_PATH.)

Best Professional Vst Plugins