Main Content

Streamline audio feature extraction

`audioFeatureExtractor`

encapsulates multiple audio feature
extractors into a streamlined and modular implementation.

creates an
audio feature extractor with default property values.`aFE`

= audioFeatureExtractor()

specifies nondefault properties for `aFE`

= audioFeatureExtractor(`Name,Value`

)`aFE`

using one or more name-value
pair arguments.

`Window`

— Analysis window`hamming(1024,"periodic")`

(default) | real vectorAnalysis window, specified as a real vector.

**Data Types: **`single`

| `double`

`OverlapLength`

— Overlap length of adjacent analysis windows`512`

(default) | integer in the range [0,
`numel(``Window`

)

)Overlap length of adjacent analysis windows, specified as an integer in the range
[0, `numel(Window)`

).

**Data Types: **`single`

| `double`

`FFTLength`

— FFT length`[]`

(default) | positive integerFFT length, specified as an integer. The default, `[]`

, means
that the FFT length is equal to the window length, (`numel(Window)`

).

**Data Types: **`single`

| `double`

`SampleRate`

— Input sample rate (Hz)`44100`

(default) | nonnegative scalarInput sample rate in Hz, specified as a nonnegative scalar.

**Data Types: **`single`

| `double`

`SpectralDescriptorInput`

— Input to spectral descriptors`"linearSpectrum"`

(default) | `"melSpectrum"`

| `"barkSpectrum"`

| `"erbSpectrum"`

Input to spectral descriptors, specified as `"linearSpectrum"`

,
`"melSpectrum"`

, `"barkSpectrum"`

, or
`"erbSpectrum"`

.

Spectral descriptors affected by this property are:

The spectrum input to the spectral descriptors is the same as output from the corresponding feature:

For example, if you set `"SpectralDescriptorInput"`

to
`"barkSpectrum"`

, and `"spectralCentroid"`

to
`true`

, then `aFE`

returns the centroid of the
default Bark
spectrum.

[audioIn,fs] = audioread('Counting-16-44p1-mono-15secs.wav'); aFE = audioFeatureExtractor("SampleRate",fs, ... "SpectralDescriptorInput","barkSpectrum", ... "spectralCentroid",true); barkSpectralCentroid = extract(aFE,audioIn);

`barkSpectrum`

using `setExtractorParams`

, then the nondefault Bark spectrum is the input to
the spectral descriptors. For example, if you call
`setExtractorParams(aFE,"barkSpectrum","NumBands",40)`

, then
`aFE`

returns the centroid of an 40-band Bark spectrum.
setExtractorParams(aFE,"barkSpectrum","NumBands",40) bark40SpectralCentroid = extract(aFE,audioIn);

**Data Types: **`char`

| `string`

`FeatureVectorLength`

— Number of features output from extractpositive integer

This property is read-only.

Total number of features output from `extract`

for the current
object configuration, specified as a positive integer.
`FeatureVectorLength`

is equal to the second dimension of the
output from the `extract`

function.

**Data Types: **`single`

| `double`

`linearSpectrum`

— Extract linear spectrum`false`

(default) | `true`

Extract the one-sided linear spectrum, specified as `true`

or
`false`

.

To set parameters of the linear spectrum extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"linearSpectrum","Name",Value)

`"FrequencyRange"`

–– Frequency range of the extracted spectrum in Hz, specified as the comma-separated pair consisting of`"FrequencyRange"`

and a two-element vector of increasing numbers in the range [0, SampleRate/2]. If unspecified,`FrequencyRange`

defaults to`[0,`

.`SampleRate`

/2]`"SpectrumType"`

–– Spectrum type, specified as the comma-separated pair consisting of`"SpectrumType"`

and`"power"`

or`"magnitude"`

. If unspecified,`SpectrumType`

defaults to`"power"`

.`"WindowNormalization"`

–– Apply window normalization, specified as the comma-separated pair consisting of`"WindowNormalization"`

and`true`

or`false`

. If unspecified,`WindowNormalization`

defaults to`true`

.

**Data Types: **`logical`

`melSpectrum`

— Extract mel spectrum`false`

(default) | `true`

Extract the one-sided mel spectrum, specified as `true`

or
`false`

.

To set parameters of the mel spectrum extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"melSpectrum","Name",Value)

`"FrequencyRange"`

–– Frequency range of the extracted spectrum in Hz, specified as the comma-separated pair consisting of`"FrequencyRange"`

and a two-element vector of increasing numbers in the range [0, SampleRate/2]. If unspecified,`FrequencyRange`

defaults to`[0,`

.`SampleRate`

/2]`"SpectrumType"`

–– Spectrum type, specified as the comma-separated pair consisting of`"SpectrumType"`

and`"power"`

or`"magnitude"`

. If unspecified,`SpectrumType`

defaults to`"power"`

.`"NumBands"`

–– Number of mel bands, specified as the comma-separated pair consisting of`"NumBands"`

and an integer. If unspecified,`NumBands`

defaults to`32`

.`"FilterBankNormalization"`

–– Normalization applied to bandpass filters, specified as the comma-separated pair consisting of`"FilterBankNormalization"`

and`"bandwidth"`

,`"area"`

, or`"none"`

. If unspecified,`FilterBankNormalization`

defaults to`"bandwidth"`

.`"WindowNormalization"`

–– Apply window normalization, specified as the comma-separated pair consisting of`"WindowNormalization"`

and`true`

or`false`

. If unspecified,`WindowNormalization`

defaults to`true`

.`"FilterBankDesignDomain"`

–– Domain in which the filter bank is designed, specified as the comma-separated pair consisting of`FilterBankDesignDomain`

and either`"linear"`

or`"warped"`

. If unspecified,`FilterBankDesignDomain`

defaults to`"linear"`

.

**Data Types: **`logical`

`barkSpectrum`

— Extract Bark spectrum`false`

(default) | `true`

Extract the one-sided Bark spectrum, specified as `true`

or
`false`

.

To set parameters of the Bark spectrum extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"barkSpectrum","Name",Value)

`"FrequencyRange"`

–– Frequency range of the extracted spectrum in Hz, specified as the comma-separated pair consisting of`"FrequencyRange"`

and a two-element vector of increasing numbers in the range [0, SampleRate/2]. If unspecified,`FrequencyRange`

defaults to`[0,`

.`SampleRate`

/2]`"SpectrumType"`

–– Spectrum type, specified as the comma-separated pair consisting of`"SpectrumType"`

and`"power"`

or`"magnitude"`

. If unspecified,`SpectrumType`

defaults to`"power"`

.`"NumBands"`

–– Number of Bark bands, specified as the comma-separated pair consisting of`"NumBands"`

and an integer. If unspecified,`NumBands`

defaults to`32`

.`"FilterBankNormalization"`

–– Normalization applied to bandpass filters, specified as the comma-separated pair consisting of`"FilterBankNormalization"`

and`"bandwidth"`

,`"area"`

, or`"none"`

. If unspecified,`FilterBankNormalization`

defaults to`"bandwidth"`

.`"WindowNormalization"`

–– Apply window normalization, specified as the comma-separated pair consisting of`"WindowNormalization"`

and`true`

or`false`

. If unspecified,`WindowNormalization`

defaults to`true`

.`"FilterBankDesignDomain"`

–– Domain in which the filter bank is designed, specified as the comma-separated pair consisting of`FilterBankDesignDomain`

and either`"linear"`

or`"warped"`

. If unspecified,`FilterBankDesignDomain`

defaults to`"linear"`

.

**Data Types: **`logical`

`erbSpectrum`

— Extract ERB spectrum`false`

(default) | `true`

Extract the one-sided ERB spectrum, specified as `true`

or
`false`

.

To set parameters of the ERB spectrum extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"erbSpectrum","Name",Value)

`"FrequencyRange"`

–– Frequency range of the extracted spectrum in Hz, specified as the comma-separated pair consisting of`"FrequencyRange"`

and a two-element vector of increasing numbers in the range [0, SampleRate/2]. If unspecified,`FrequencyRange`

defaults to`[0,`

.`SampleRate`

/2]`"SpectrumType"`

–– Spectrum type, specified as the comma-separated pair consisting of`"SpectrumType"`

and`"power"`

or`"magnitude"`

. If unspecified,`SpectrumType`

defaults to`"power"`

.`"NumBands"`

–– Number of ERB bands, specified as the comma-separated pair consisting of`"NumBands"`

and an integer. If unspecified,`NumBands`

defaults to`ceil(`

.`hz2erb`

(FrequencyRange(2))-`hz2erb`

(FrequencyRange(1)))`"FilterBankNormalization"`

–– Normalization applied to bandpass filters, specified as the comma-separated pair consisting of`"FilterBankNormalization"`

and`"bandwidth"`

,`"area"`

, or`"none"`

. If unspecified,`FilterBankNormalization`

defaults to`"bandwidth"`

.`"WindowNormalization"`

–– Apply window normalization, specified as the comma-separated pair consisting of`"WindowNormalization"`

and`true`

or`false`

. If unspecified,`WindowNormalization`

defaults to`true`

.

**Data Types: **`logical`

`mfcc`

— Extract mel-frequency cepstral coefficients (MFCC)`false`

(default) | `true`

Extract mel-frequency cepstral coefficients (MFCC), specified as
`true`

or `false`

.

To set parameters of the MFCC extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"mfcc","Name",Value)

`"NumCoeffs"`

–– Number of coefficients returned for each window, specified as a the comma-separated pair consisting of`"NumCoeffs"`

and a positive integer. If unspecified,`NumCoeffs`

defaults to`13`

.`"DeltaWindowLength"`

–– Delta window length, specified as the comma-separated pair consisting of`"DeltaWindowLength"`

and an odd integer greater than 2. If unspecified,`DeltaWindowLength`

defaults to`9`

. This parameter affects the`mfccDelta`

and`mfccDeltaDelta`

features.`"Rectification"`

–– Type of nonlinear rectification, specified as the comma-separated pair consisting of`"Rectification"`

and`"log"`

or`"cubic-root"`

.

The mel-frequency cepstral coefficients are calculated using the melSpectrum.

**Data Types: **`logical`

`mfccDelta`

— Extract delta of MFCC`false`

(default) | `true`

Extract delta of MFCC, specified as `true`

or
`false`

.

The delta MFCC is calculated based on the extracted MFCC. Parameters set on
`mfcc`

affect `mfccDelta`

.

**Data Types: **`logical`

`mfccDeltaDelta`

— Extract delta-delta of MFCC`false`

(default) | `true`

Extract delta-delta of MFCC, specified as `true`

or
`false`

.

The delta-delta MFCC is calculated based on the extracted MFCC. Parameters set on
`mfcc`

affect `mfccDeltaDelta`

.

**Data Types: **`logical`

`gtcc`

— Extract gammatone cepstral coefficients (GTCC)`false`

(default) | `true`

Extract gammatone cepstral coefficients (GTCC), specified as
`true`

or `false`

.

To set parameters of the GTCC extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"gtcc","Name",Value)

`"NumCoeffs"`

–– Number of coefficients returned for each window, specified as a the comma-separated pair consisting of`"NumCoeffs"`

and a positive integer. If unspecified,`NumCoeffs`

defaults to`13`

.`"DeltaWindowLength"`

–– Delta window length, specified as the comma-separated pair consisting of`"DeltaWindowLength"`

and an odd integer greater than 2. If unspecified,`DeltaWindowLength`

defaults to`9`

. This parameter affects the`gtccDelta`

and`gtccDeltaDelta`

features.

`"Rectification"`

–– Type of nonlinear rectification, specified as the comma-separated pair consisting of`"Rectification"`

and`"log"`

or`"cubic-root"`

.

The gammatone cepstral coefficients are calculated using the erbSpectrum.

**Data Types: **`logical`

`gtccDelta`

— Extract delta of GTCC`false`

(default) | `true`

Extract delta of GTCC, specified as `true`

or
`false`

.

The delta GTCC is calculated based on the extracted GTCC. Parameters set on
`gtcc`

affect `gtccDelta`

.

**Data Types: **`logical`

`gtccDeltaDelta`

— Extract delta-delta of GTCC`false`

(default) | `true`

Extract delta-delta of GTCC, specified as `true`

or
`false`

.

The delta-delta GTCC is calculated based on the extracted GTCC. Parameters set on
`gtcc`

affect `gtccDeltaDelta`

.

**Data Types: **`logical`

`spectralCentroid`

— Extract spectral centroid`false`

(default) | `true`

Extract spectral centroid, specified as `true`

or
`false`

.

The spectral centroid is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`spectralCrest`

— Extract spectral crest`false`

(default) | `true`

Extract spectral crest, specified as `true`

or
`false`

.

The spectral crest is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`spectralDecrease`

— Extract spectral decrease`false`

(default) | `true`

Extract spectral decrease, specified as `true`

or
`false`

.

The spectral decrease is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`spectralEntropy`

— Extract spectral entropy`false`

(default) | `true`

Extract spectral entropy, specified as `true`

or
`false`

.

The spectral entropy is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`spectralFlatness`

— Extract spectral flatness`false`

(default) | `true`

Extract spectral flatness, specified as `true`

or
`false`

.

The spectral flatness is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`spectralFlux`

— Extract spectral flux`false`

(default) | `true`

Extract spectral flux, specified as `true`

or
`false`

.

The spectral flux is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

To set parameters of the spectral flux extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"spectralFlux","Name",Value)

`"NormType"`

–– Norm type used to calculate the spectral flux, specified as the comma-separated pair consisting of`"NormType"`

and a`1`

or`2`

. If unspecified,`NormType`

defaults to`2`

.

**Data Types: **`logical`

`spectralKurtosis`

— Extract spectral kurtosis`false`

(default) | `true`

Extract spectral kurtosis, specified as `true`

or
`false`

.

The spectral kurtosis is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`spectralRolloffPoint`

— Extract spectral rolloff point`false`

(default) | `true`

Extract spectral rolloff point, specified as `true`

or
`false`

.

The spectral rolloff point is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

To set parameters of the spectral rolloff point extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"spectralRolloffPoint","Name",Value)

`"Threshold"`

–– Threshold of the rolloff point, specified as the comma-separated pair consisting of`"Threshold"`

and a scalar in the range (0, 1). If unspecified,`Threshold`

defaults to`0.95`

.

**Data Types: **`logical`

`spectralSkewness`

— Extract spectral skewness`false`

(default) | `true`

Extract spectral skewness, specified as `true`

or
`false`

.

The spectral skewness is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`spectralSlope`

— Extract spectral slope`false`

(default) | `true`

Extract spectral slope, specified as `true`

or
`false`

.

The spectral slope is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`spectralSpread`

— Extract spectral spread`false`

(default) | `true`

Extract spectral spread, specified as `true`

or
`false`

.

The spectral spread is calculated on one of the following spectral representations, as specified by the SpectralDescriptorInput property:

**Data Types: **`logical`

`pitch`

— Extract pitch`false`

(default) | `true`

Extract pitch, specified as `true`

or
`false`

.

To set parameters of the pitch extraction, use `setExtractorParams`

:

setExtractorParams(aFE,"pitch","Name",Value)

`"Method"`

–– Method used to calculate the pitch, specified as the comma-separated pair consisting of`"Method"`

and`"PEF"`

,`"NCF"`

,`"CEP"`

,`"LHS"`

, or`"SRH"`

. If unspecified,`Method`

defaults to`"NCF"`

. For a description of available pitch extraction methods, see`pitch`

.`"Range"`

–– Range within to search for the pitch in Hz, specified as the comma-separated pair consisting of`"Range"`

and a two-element row vector of increasing values. If unspecified,`Range`

defaults to`[50,400]`

.`"MedianFilterLength"`

–– Median filter length used to smooth pitch estimates over time, specified as the comma-separated pair consisting of`"MedianFilterLength"`

and a positive integer. If unspecified,`MedianFilterLength`

defaults to`1`

(no median filtering).

**Data Types: **`logical`

`harmonicRatio`

— Extract harmonic ratio`false`

(default) | `true`

Extract harmonic ratio, specified as `true`

or
`false`

.

**Data Types: **`logical`

`extract` | Extract audio features |

`setExtractorParams` | Set nondefault parameter values for individual feature extractors |

`info` | Output mapping and individual feature extractor parameters |

`generateMATLABFunction` | Create MATLAB function compatible with C/C++ code generation |

Read in an audio signal.

`[audioIn,fs] = audioread("Counting-16-44p1-mono-15secs.wav");`

Create an `audioFeatureExtractor`

object that extracts the MFCC, delta MFCC, delta-delta MFCC, pitch, and spectral centroid of an audio signal. Use a 30 ms analysis window with 20 ms overlap.

aFE = audioFeatureExtractor( ... "SampleRate",fs, ... "Window",hamming(round(0.03*fs),"periodic"), ... "OverlapLength",round(0.02*fs), ... "mfcc",true, ... "mfccDelta",true, ... "mfccDeltaDelta",true, ... "pitch",true, ... "spectralCentroid",true);

Call `extract`

to extract the audio features from the audio signal.

features = extract(aFE,audioIn);

Use `info`

to determine which column of the feature extraction matrix corresponds to the requested pitch extraction.

idx = info(aFE)

`idx = `*struct with fields:*
mfcc: [1 2 3 4 5 6 7 8 9 10 11 12 13]
mfccDelta: [14 15 16 17 18 19 20 21 22 23 24 25 26]
mfccDeltaDelta: [27 28 29 30 31 32 33 34 35 36 37 38 39]
spectralCentroid: 40
pitch: 41

Plot the detected pitch over time.

t = linspace(0,size(audioIn,1)/fs,size(features,1)); plot(t,features(:,idx.pitch)) title('Pitch') xlabel('Time (s)') ylabel('Frequency (Hz)')

Create an audio datastore that points to audio samples included with Audio Toolbox®.

folder = fullfile(matlabroot,'toolbox','audio','samples'); ads = audioDatastore(folder);

Find all files that correspond to a sample rate of 44.1 kHz and then `subset`

the datastore.

```
keepFile = cellfun(@(x)contains(x,'44p1'),ads.Files);
ads = subset(ads,keepFile);
```

Convert the data to a `tall`

array. `tall`

arrays are evaluated only when you request them explicitly using `gather`

. MATLAB® automatically optimizes the queued calculations by minimizing the number of passes through the data. If you have Parallel Computing Toolbox™, you can spread the calculations across multiple machines. The audio data is represented as an *M*-by-1 tall cell array, where *M* is the number of files in the audio datastore.

adsTall = tall(ads)

Starting parallel pool (parpool) using the 'local' profile ... Connected to the parallel pool (number of workers: 6). adsTall = M×1 tall cell array { 539648×1 double} { 227497×1 double} { 8000×1 double} { 685056×1 double} { 882688×2 double} {1115760×2 double} { 505200×2 double} {3195904×2 double} : : : :

Create an `audioFeatureExtractor`

object to extract the mel spectrum, Bark spectrum, ERB spectrum, and linear spectrum from each audio file. Use the default analysis window and overlap length for the spectrum extraction.

aFE = audioFeatureExtractor('SampleRate',44.1e3, ... 'melSpectrum',true, ... 'barkSpectrum',true, ... 'erbSpectrum',true, ... 'linearSpectrum',true);

Define a `cellfun`

function so that audio features are extracted from each cell of the tall array. Call `gather`

to evaluate the tall array.

```
specsTall = cellfun(@(x)extract(aFE,x),adsTall,"UniformOutput",false);
specs = gather(specsTall);
```

Evaluating tall expression using the Parallel Pool 'local': - Pass 1 of 1: Completed in 12 sec Evaluation completed in 12 sec

The `specs`

variable returned from gather is a *numFiles*-by-1 cell array, where *numFiles* is the number of files in the datastore. Each element of the cell array is a *numHops*-by-*numFeatures*-by-*numChannels* array, where the number of hops and number of channels depends on the length and number of channels of the audio file, and the number of features is the requested number of features from the audio data.

numFiles = numel(specs)

numFiles = 12

[numHops1,numFeaturesFile1,numChanelsFile1] = size(specs{1})

numHops1 = 1053

numFeaturesFile1 = 620

numChanelsFile1 = 1

[numHops2,numFeaturesFile2,numChanelsFile2] = size(specs{2})

numHops2 = 443

numFeaturesFile2 = 620

numChanelsFile2 = 1

The `audioFeatureExtractor`

creates a feature extraction pipeline based on
your selected features. To reduce computations, `audioFeatureExtractor`

reuses
intermediary representations. Some intermediate representations can be output as
features:

For example, to create an object that extracts the centroid of the Bark spectrum, the flux
of the Bark spectrum, the pitch, the harmonic ratio, and the delta-delta of the MFCC, specify
the `audioFeatureExtractor`

as:

aFE = audioFeatureExtractor( ... "SpectralDescriptorInput","barkSpectrum", ... "spectralCentroid",true, ... "spectralFlux",true, ... "pitch",true, ... "harmonicRatio",true, ... "mfccDeltaDelta",true)

aFE = audioFeatureExtractor with properties: Properties Window: [1024×1 double] OverlapLength: 512 SampleRate: 44100 FFTLength: [] SpectralDescriptorInput: 'barkSpectrum' Enabled Features mfccDeltaDelta, spectralCentroid, spectralFlux, pitch, harmonicRatio Disabled Features linearSpectrum, melSpectrum, barkSpectrum, erbSpectrum, mfcc, mfccDelta gtcc, gtccDelta, gtccDeltaDelta, spectralCrest, spectralDecrease, spectralEntropy spectralFlatness, spectralKurtosis, spectralRolloffPoint, spectralSkewness, spectralSlope, spectralSpread To extract a feature, set the corresponding property to true. For example, obj.mfcc = true, adds mfcc to the list of enabled features.

**Note**

Because `audioFeatureExtractor`

reuses intermediary representations, the
features output from `audioFeatureExtractor`

may not correspond with the
default configuration of features output by corresponding individual feature
extractors.

*Behavior changed in R2020b*

The `audioDelta`

function is now used to compute `mfccDelta`

,
`mfccDeltaDelta`

, `gtccDelta`

, and
`gtccDeltaDelta`

. The `audioDelta`

algorithm has a
different startup behavior than the previous algorithm. The default window length used to
compute the deltas has changed from `2`

to `9`

. A delta
window length of `2`

is no longer supported.

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

You cannot generate code directly from

`audioFeatureExtractor`

. You can generated C/C++ code from the function returned by`generateMATLABFunction`

.

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Usage notes and limitations:

The

`pitch`

property is not supported.

For an overview of GPU usage in MATLAB^{®}, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Extract Audio
Features | `audioDatastore`

| `audioDataAugmenter`

| Audio Labeler | `vggishFeatures`

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