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Descriptors

  • barkSpecFlux~ The barkSpecFlux~ object calculates the spectral flux of an audio signal based on Bark-band energy differences.
  • fluid.bufaudiotransport fluid.bufaudiotransport analyzes two source audio buffers using FFT to derive spectral characteristics.
  • fluid.stats The fluid.stats object calculates the rolling mean and sample standard deviation for multichannel control inputs over a specified window.
  • bark~ The bark~ object is a real-time onset detector for Pure Data, which analyzes spectral growth using the perceptually-based Bark frequency scale.
  • specKurtosis The specKurtosis object calculates the spectral kurtosis of an audio array, serving as a non-real-time spectral descriptor.
  • barkSpec~ The barkSpec~ object analyzes incoming audio to compute its Bark-frequency spectrum, which warps the normal spectrum to the Bark scale, emphasizing low-frequency detail.
  • dct~ The dct~ object computes the Discrete Cosine Transform (DCT) of an incoming audio window, outputting a list of real numbers representing its spectral characteristics.
  • cepstrum The cepstrum object computes the cepstrum of an audio signal from a specified sample array.
  • fluid.bufmfcc The fluid.bufmfcc object calculates Mel-Frequency Cepstral Coefficients (MFCCs), a classic timbral spectral descriptor.
  • fluid.bufnoveltyfeature The fluid.bufnoveltyfeature object calculates a novelty curve from audio data stored in a buffer.
  • barkSpecFlatness~ The barkSpecFlatness~ object calculates the spectral flatness of an incoming audio signal within the Bark frequency scale, outputting a value between 0.0 and 1.0 that indicates how noise-like the spectrum is.
  • minSample The minSample object analyzes a specified window within a Pure Data array, typically containing audio samples.
  • rms~ The rms~ object calculates the Root Mean Square (RMS) value of an incoming audio signal, similar to env~ but providing RMS in linear amplitude or dBFS.
  • waveSlope The waveSlope object analyzes the slope of a waveform stored in a Pure Data array.
  • specCentroid The specCentroid object calculates the spectral centroid of an audio array, providing a measure of the 'brightness' or 'timbral richness' of a sound.
  • specFlux~ The specFlux~ object calculates the spectral flux of an audio signal, quantifying how quickly its spectrum changes over time.
  • meter~ The meter~ object functions as a convenient mono VU-meter, analyzing an incoming audio signal.
  • roughness The roughness object estimates the psychoacoustic roughness of an audio spectrum in real-time, often utilizing the output of sigmund.
  • fluid.onsetslice~ The fluid.onsetslice~ object performs spectrum-based onset detection on audio signals.
  • zeroCrossing The zeroCrossing object calculates the zero-crossing rate of a specified audio array or a segment of it.
  • barkSpecBrightness~ The barkSpecBrightness~ object calculates the brightness of an audio signal's Bark spectrum.
  • specBrightness~ The specBrightness~ object calculates the spectral brightness of an audio signal, defined as the ratio of high-frequency spectral magnitudes to total spectral magnitudes.
  • pix_histo pix_histo calculates the histogram (density function) of an input image, storing the results in Pure Data tables.
  • barks~ The barks~ object analyzes sound files to extract energy information across critical bands on the Bark scale.
  • minSampleDelta The minSampleDelta object analyzes a specified window within a sample array to find the smallest absolute difference between consecutive samples.
  • fluid.bufloudness The fluid.bufloudness object computes two loudness descriptors: true peak and a loudness measurement that applies broadcasting standard filters to emulate perceived amplitude.
  • irmeasure~ The irmeasure~ object is designed for measuring Impulse Responses (IRs) of acoustic systems using various test signals like Exponential Sine Sweeps (ESS), maximum length sequences, or different types of noise.
  • fluid.pitch~ fluid.pitch~ is a monophonic pitch descriptor that computes both the fundamental frequency and a confidence score from an audio input.
  • sampleBuffer~ The sampleBuffer~ object buffers incoming audio, providing a windowed segment of the audio stream for real-time analysis.
  • autoCorrPitch The autoCorrPitch object performs offline pitch tracking on a specified audio sample array using an autocorrelation algorithm.
  • fluid.loudness~ The fluid.loudness~ object calculates two audio descriptors: loudness and peak.
  • maxSample~ The maxSample~ object reports the maximum sample value and its corresponding index within a specified audio window.
  • spectrograph~ The spectrograph~ object visualizes FFT amplitudes from 0 Hz to Nyquist, using a Hann window for spectral analysis.
  • specSlope The specSlope object calculates the spectral slope of an audio sample, quantifying the average decrease in amplitude across increasing frequencies.
  • fluid.bufonsetslice fluid.bufonsetslice implements various spectrum-based onset detection algorithms on audio data stored in a buffer.
  • maxpeak~ The maxpeak~ object continuously monitors an audio signal and outputs its maximum peak amplitude observed so far, either in decibels or linear scale.
  • specSlope~ The specSlope~ object calculates the spectral slope of an incoming audio signal, representing the slope of the best-fit line through its magnitude spectrum.
  • barkSpecFlux The barkSpecFlux object calculates the spectral flux between two audio windows (forward and back) based on their Bark band energy differences.
  • fluid.ampfeature~ The fluid.ampfeature~ object calculates various amplitude differential features from an audio signal.
  • fluid.bufspectralshape The fluid.bufspectralshape object computes seven spectral shape descriptors (centroid, spread, skewness, kurtosis, rolloff, flatness, crest) from an audio source.
  • sharpness~ The sharpness~ object measures the psychoacoustic sharpness of an audio signal.
  • meter8~ The else/meter8~ object functions as an 8-channel VU meter, providing RMS and peak amplitude values in dBFS for incoming audio signals.
  • phaseSpec The phaseSpec object from timbreIDLib calculates the phase spectrum of a specified window within an audio sample array.
  • barkSpecCentroid The barkSpecCentroid object computes the Bark spectrum centroid, a psychoacoustically weighted measure of an audio signal's spectral balance.
  • fluid.melbands~ The fluid.melbands~ object calculates the magnitudes of audio signals across a specified number of perceptually evenly spread Mel-frequency bands.
  • bfcc The bfcc object computes Bark-frequency Cepstral Coefficients, which are a common audio descriptor used to characterize timbre.
  • phaseSpec~ The phaseSpec~ object calculates and outputs the phase spectrum of an audio signal.
  • maxSampleDelta~ The maxSampleDelta~ object analyzes an audio stream to find the largest absolute difference between adjacent samples within a specified window.
  • chroma~ The chroma~ object analyzes incoming audio to determine the spectral energy present in each of the 12 musical pitch classes, regardless of octave.
  • fluid.spectralshape~ fluid.spectralshape~ computes seven spectral shape descriptors from an audio signal: centroid, spread, skewness, kurtosis, rolloff, flatness, and crest.
  • tonalness The tonalness object calculates the pitch clarity of an audio spectrum, providing measures for both pure and complex tones.
  • distance The distance object calculates the perceptual distance between pitches.
  • barkSpecRolloff The barkSpecRolloff object calculates the spectral rolloff of an audio signal based on its Bark scale spectrum.
  • energyEntropy The energyEntropy object calculates the energy entropy of an audio sample array.
  • fluid.bufmelbands fluid.bufmelbands computes the magnitudes for a specified number of perceptually-evenly spaced mel bands from an audio buffer.
  • fluid.bufselect The fluid.bufselect~ object copies specific sets of values from a buffer, allowing selection by channels and indices.
  • roughcurve The roughcurve object is an abstraction that generates curves representing psychoacoustic roughness and spectral scales.
  • peak~ The peak~ object analyzes an incoming audio signal to report its peak amplitude.
  • barkSpecIrregularity~ The barkSpecIrregularity~ object calculates the spectral irregularity of an audio signal's Bark spectrum.
  • harmonicRatio The 'harmonicRatio' object calculates the harmonic ratio of a specified audio sample array or a window within it.
  • specIrregularity~ The specIrregularity~ object calculates the spectral irregularity of an audio signal, indicating how jagged or smooth its frequency spectrum is.
  • waveNoise~ The waveNoise~ object measures the noisiness of an audio signal by counting the number of times the signal changes direction within a specified window.
  • envrms~ The envrms~ object is an envelope follower designed for audio signals.
  • fluid.datasetquery The fluid.datasetquery object allows users to query and filter FluidDataSet objects.
  • cepstrumPitch~ The cepstrumPitch~ object performs real-time pitch tracking of an audio signal using cepstrum analysis.
  • specRolloff The specRolloff object calculates the spectral rolloff of an audio signal, identifying the frequency below which a specified percentage of the total spectral energy lies.
  • tID_mean The tID_mean object calculates the arithmetic mean of a list of numbers.
  • vu~ The vu~ object analyzes an incoming audio signal, providing both its RMS (Root Mean Square) amplitude and peak amplitude, expressed in dBFS.
  • detect~ The detect~ object measures the time or frequency between incoming trigger signals.
  • barkSpecSlope~ The barkSpecSlope~ object calculates the slope of the best-fit line through the data points of a Bark spectrum.
  • barkSpecBrightness The barkSpecBrightness object calculates the brightness of an audio sample by analyzing its Bark spectrum.
  • fluid.transients~ fluid.transients~ is a real-time audio object that models and separates transients from its input signal.
  • tID_fft The tID_fft object performs an offline Fast Fourier Transform (FFT) on a specified segment of an audio sample array in Pure Data.
  • hann~ The hann~ object applies a Hann window to an incoming audio signal.
  • al The al object calculates the Audible Level AL(P) in dB, taking into account a masking stage.
  • beat~ The beat~ object analyzes an input audio signal to detect its tempo and output a detected BPM value.
  • zeroCrossing~ The zeroCrossing~ object measures the noisiness or frequency-related characteristics of an audio signal by counting how many times it crosses the zero amplitude point within a specified window.
  • fluid.mfcc~ The fluid.mfcc~ object calculates Mel-Frequency Cepstral Coefficients (MFCCs) in real-time, serving as a classic timbral audio descriptor.
  • bark The bark object is a non-real-time audio onset detector that identifies musical attacks by analyzing spectral changes.
  • salience The salience object analyzes an audio spectrum to calculate its tone salience and multiplicity.
  • energyEntropy~ The energyEntropy~ object measures abrupt changes in the energy of an audio signal.
  • range The range~ object analyzes an incoming signal (float or signal) to determine its minimum and maximum values.
  • barkSpecSlope The barkSpecSlope object calculates the slope of the Bark spectrum for a given audio segment.
  • energy The energy object from the timbreIDLib library calculates the energy of a specified audio sample array or a segment within it.
  • range~ The range~ object analyzes an incoming audio signal and continuously outputs its minimum and maximum amplitude values.
  • tabletool The tabletool object provides a comprehensive set of functionalities for manipulating, analyzing, and querying data stored in Pure Data tables.
  • barkSpecKurtosis The barkSpecKurtosis object calculates the kurtosis of the Bark spectrum, serving as an audio descriptor within the timbreIDLib.
  • fluid.audiotransport~ The fluid.audiotransport~ object performs spectral interpolation between two loaded audio sounds.
  • pix_blobtracker The pix_blobtracker object in Pure Data is a video analysis tool designed to detect and track multiple distinct regions (blobs) within an incoming video stream.
  • magSpec The magSpec object from the timbreIDLib library performs non-real-time spectral analysis on a given audio sample array.
  • minSample~ The minSample~ object reports the value and index of the smallest sample within a configurable N-sample window of incoming audio.
  • meter4~ meter4~ is a convenient quadraphonic VU-meter abstraction that measures the RMS and peak amplitude (in dBFS) of four incoming audio channels.
  • barkSpecSkewness The barkSpecSkewness object calculates the skewness of the Bark spectrum of an audio sample.
  • fluid.bufonsetfeature The fluid.bufonsetfeature object calculates various spectral difference features and metrics from an audio buffer, such as Energy, HFC, and SpectralFlux.
  • waveSlope~ The waveSlope~ object calculates the slope of the best-fit line through the absolute value of audio samples within a configurable analysis window.
  • cepstrumPitch The cepstrumPitch object performs offline pitch tracking on an audio sample array using cepstral analysis.
  • fluid.bufnoveltyslice The fluid.bufnoveltyslice object is a non-realtime audio slicer that identifies segmentation points in a source buffer (srcBuf) by assessing signal novelty.
  • fluid.bufpitch fluid.bufpitch computes three popular pitch descriptors (frequency and confidence) from an audio buffer.
  • tID_std The tID_std object calculates the standard deviation of a list of numbers, requiring at least two elements.
  • specKurtosis~ The specKurtosis~ object calculates the spectral kurtosis of an audio signal, quantifying the peakedness of its spectrum.
  • featureDelta The featureDelta object calculates the difference between corresponding attributes of two incoming feature lists, such as audio descriptors.
  • specRolloff~ The specRolloff~ object calculates the spectral rolloff frequency of an audio signal, representing the frequency below which a specified percentage of the total spectral energy is concentrated.
  • fluid.bufnmf The fluid.bufnmf object performs Non-Negative Matrix Factorisation (NMF) to decompose the spectrum of a sound into multiple components, represented by 'bases' (spectral profiles) and 'activations' (temporal envelopes).
  • barkSpecSpread The barkSpecSpread object calculates the Bark spectrum spread, a measure of the spectral width of an audio signal based on the Bark scale.
  • fluid.bufnmfseed The fluid.bufnmfseed object computes initial bases and activations for Non-negative Matrix Factorization (NMF) from an input audio buffer.
  • specBrightness The specBrightness object from the timbreIDLib analyzes the spectral brightness of an audio sample.
  • zerox~ The zerox~ object detects and counts zero crossings in an audio signal.
  • barkSpec The barkSpec object calculates the Bark spectrum of an audio sample or a specified segment within a sample array.
  • barkSpecCentroid~ The barkSpecCentroid~ object calculates the Bark spectrum centroid, representing the "center of mass" of an audio signal's energy distribution on the Bark frequency scale.
  • cepstrum~ The cepstrum~ object computes the real cepstrum of an audio signal, derived from the Inverse Fourier Transform of the log magnitude spectrum.
  • fluid.nmfmatch~ The fluid.nmfmatch~ object matches an incoming audio signal against a set of spectral templates, typically derived using Non-negative Matrix Factorization (NMF).
  • melSpec The 'melSpec' object computes a Mel-scaled spectrogram from an audio sample, providing a time-frequency representation of sound.
  • fluid.bufhpss The fluid.bufhpss object performs Harmonic-Percussive Source Separation (HPSS) on audio stored in buffers.
  • fluid.onsetfeature~ fluid.onsetfeature~ calculates spectral difference features from an audio signal, primarily for use with fluid.onsetslice~.
  • specIrregularity The specIrregularity object calculates the spectral irregularity of an audio signal, providing a numerical descriptor of its timbral characteristics.
  • specHarmonicity The specHarmonicity object calculates the spectral harmonicity and inharmonicity of an audio sample.
  • minSampleDelta~ The minSampleDelta~ object calculates the minimum absolute difference between adjacent samples within a specified audio window.
  • barkSpecIrregularity The barkSpecIrregularity object computes the Bark spectrum irregularity of an audio signal, a descriptor indicating the noisiness or irregularity of its spectral envelope.
  • specFlatness~ The specFlatness~ object calculates the spectral flatness of an incoming audio signal, providing a measure of how noise-like a sound is.
  • waveNoise The waveNoise object analyzes a specified sample array to quantify its "noisiness" or the rate of change in its waveform direction.
  • dct The dct object computes the Discrete Cosine Transform (DCT) of a specified portion or the entirety of a Pure Data array.
  • maxSampleDelta The maxSampleDelta object analyzes a specified segment of a sample array to identify the largest absolute difference between consecutive samples.
  • chroma The chroma object performs non-real-time pitch chroma analysis on audio data stored in a Pure Data array.
  • tID_fft~ The tID_fft~ object computes the complex Fast Fourier Transform (FFT) of an audio signal, triggered by a bang.
  • peakamp~ The peakamp~ object reports the absolute peak amplitude of an audio signal since its last output.
  • attackTime~ The attackTime~ object calculates the attack time of an audio event in milliseconds.
  • barkSpecKurtosis~ The barkSpecKurtosis~ object calculates the kurtosis (peakedness) of an audio signal's Bark spectrum.
  • fluid.transientslice~ fluid.transientslice~ is a real-time audio analysis object that extracts slices from an incoming audio stream based on transient detection.
  • pvoc~ The pvoc~ object performs phase vocoding, a technique for time-stretching or pitch-shifting audio by analyzing its frequency content.
  • nearestPoint The nearestPoint object identifies the closest point(s) within a stored dataset to a given input point in a multi-dimensional space.
  • fluid.bufstats The fluid.bufstats object calculates various statistical descriptors (e.g., mean, standard deviation, skewness, kurtosis, pitch) from segments within an audio buffer.
  • specCentroid~ The specCentroid~ object calculates the spectral centroid, a low-level timbre feature representing the "center of mass" of an audio signal's magnitude spectrum.
  • mfcc The mfcc object calculates Mel-Frequency Cepstral Coefficients (MFCCs) from an audio sample array, providing a compact representation of the spectral envelope.
  • peakSample The peakSample object analyzes a specified audio array or a segment of it to find the maximum sample value and its corresponding index.
  • timbreID The timbreID object stores, clusters, and classifies audio feature vectors, enabling tasks like sound identification and timbre ordering.
  • centroid~ The centroid~ object calculates the spectral centroid of an audio signal, representing the 'center of gravity' of its frequency spectrum.
  • maxSample The maxSample object analyzes a specified portion of a Pure Data array (typically containing audio samples) to find the maximum sample value and its corresponding index within that segment.
  • specSpread The specSpread object calculates the spectral spread, a measure of the dispersion of the spectrum around its centroid, for an audio signal stored in a Pure Data array.
  • bfcc~ The bfcc~ object computes Bark-frequency cepstral coefficients (BFCCs) from an audio input, emphasizing lower spectral content and using a Discrete Cosine Transform.
  • tID-conversion This Pure Data object provides essential conversion utilities for audio frequency analysis.
  • specSkewness The specSkewness object from the timbreIDLib calculates the spectral skewness of an audio sample array.
  • mov.rms~ The mov.rms~ object calculates a running Root Mean Square (RMS) of an audio signal over a specified time window (number of samples).
  • featureNorm The featureNorm object normalizes incoming feature lists, scaling their values to a specified range (either 0 to 1 by default, or -1 to 1).
  • specHarmonicity~ The specHarmonicity~ object quantifies the harmonic alignment of spectral peaks in an audio signal, outputting both harmonicity and inharmonicity values between 0 and 1.
  • specFlatness The specFlatness object calculates the spectral flatness of an audio array, providing a measure of its noisiness.
  • fluid.noveltyslice~ The fluid.noveltyslice~ object is a real-time audio slicer that detects "novelty" in an incoming signal to determine slicing points.
  • energy~ The energy~ object from timbreIDLib continuously calculates the energy of an audio signal, offering output in power, RMS, or decibels with adjustable window sizing and normalization.
  • fluid.bufampfeature The fluid.bufampfeature object calculates an amplitude differential feature from an audio buffer, useful for tasks like event detection or slicing.
  • pix_drum The pix_drum object analyzes incoming video streams, specifically detecting black pixels from the top of the image.
  • fluid.ampslice~ The fluid.ampslice~ object performs amplitude-based segmentation of audio signals.
  • barkSpecRolloff~ The barkSpecRolloff~ object calculates the Bark spectrum rolloff, which is the Bark frequency below which a specified concentration of spectral energy is located.
  • harmonicRatio~ The harmonicRatio~ object calculates the harmonic ratio of an audio signal, providing an indicator of its periodicity.
  • barkSpecSpread~ The barkSpecSpread~ object calculates the spread of an audio signal's Bark spectrum, indicating the concentration of energy around its centroid.
  • barkSpecSkewness~ The barkSpecSkewness~ object calculates the skewness of an audio signal's Bark spectrum, quantifying the symmetry of its energy distribution across frequency bands.
  • magSpec~ The magSpec~ object calculates the magnitude spectrum of an incoming audio signal over a specified window.
  • fluid.chroma~ The fluid.chroma~ object analyzes an audio input to compute a histogram of energy across different pitch classes.
  • barkSpecFlatness The barkSpecFlatness object calculates the spectral flatness of an audio signal within Bark-scaled frequency bands.
  • fluid.bufchroma The fluid.bufchroma object computes a histogram of the energy contained within audio signals, specifically focusing on chroma features.
  • attackTime The attackTime object analyzes a specified segment of a sound sample array to determine its attack time.
  • peakSample~ The peakSample~ object identifies the sample with the largest magnitude within a defined window of an incoming audio signal, outputting both its value and index.
  • specSpread~ The specSpread~ object calculates the spectral spread of an audio signal, quantifying the concentration of its energy around the spectral centroid in Hz.
  • fluid.noveltyfeature~ The fluid.noveltyfeature~ object calculates the novelty feature of audio in real-time, indicating changes in underlying audio characteristics.
  • specSkewness~ The specSkewness~ object calculates the spectral skewness of an audio signal, providing a measure of the asymmetry of its spectral envelope.
  • fluid.buftransientslice The fluid.buftransientslice object extracts transient-based slices from audio buffers.
  • mfcc~ The mfcc~ object computes Mel-Frequency Cepstral Coefficients from an audio signal, emphasizing lower spectral content and using a Discrete Cosine Transform.
  • dfreq~ The dfreq~ object is a computationally efficient frequency detector that estimates the frequency of an incoming audio signal by counting zero-crossings.
  • fluid.bufsinefeature The fluid.bufsinefeature object performs interpolated sinusoidal peak tracking on the spectrum of audio data stored in a buffer.
  • mag~ The mag~ object calculates the magnitude (amplitude) of a signal from its real and imaginary components, functioning similarly to the amplitude output of car2pol~.
  • specFlux The specFlux object calculates spectral flux, a measure of how quickly the spectrum of a sound is changing.
  • featureAccum The featureAccum object accumulates incoming lists of feature frames, processing them into a single output based on a specified mode.
  • melSpec~ The melSpec~ object computes the Mel-frequency spectrum of an incoming audio signal, transforming the linear frequency scale to the perceptually-motivated mel scale.
  • morphine~ morphine~ performs spectral morphing, enabling a smooth transition between two audio signals in the frequency domain.
  • pix_multiblob The pix_multiblob object detects multiple "blobs" within an image, defined as adjacent pixels exceeding a specified luminance threshold and minimum blobSize.
  • fluid.bufstft The fluid.bufstft object performs forward and inverse Short-Time Fourier Transforms (STFT) on single-channel audio buffers.
  • zerocross~ The zerocross~ object detects zero crossings in an audio signal.
  • autoCorrPitch~ The autoCorrPitch~ object calculates the fundamental pitch of an incoming audio signal using autocorrelation, converting the result to Hertz and MIDI units.
  • binWrangler The binWrangler Pure Data object accumulates a specified number of feature vector frames, such as BFCCs, and then outputs the time-varying information organized by bin number as a concatenated list.