Auditory Spectrogram

Extract mel, Bark, or ERB spectrogram from audio

Since R2022a

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  • Auditory Spectrogram block

Libraries:
Audio Toolbox / Features

Description

The Auditory Spectrogram block extracts a spectrogram from the audio input signal. A spectrogram contains an estimate of the short-term, time-localized frequency content of the input signal.

Examples

Extract Auditory Spectrogram

Extract Auditory Spectrogram

Extract a spectrogram using the Auditory Spectrogram block.

Extract GTCC from Audio in Simulink

Extract GTCC from Audio in Simulink

Extract gammatone cepstral coefficients and their delta features in Simulink®.

Ports

Input

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Audio input signal, specified as a column vector or a matrix. When you specify a matrix, the block treats columns as independent audio channels.

Data Types: single | double

Output

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Spectrogram, returned as a matrix or 3-D array. The dimensions of spec are L-by-M-by-N, where:

  • L is the number of spectra, which is determined by the Number of spectra parameter.

  • M is the number of bands, which is determined by the Auto-determine number of bands and Number of bands parameters.

  • N is the number of channels in the input audio signal.

Trailing singleton dimensions are removed from the output.

This port is unnamed until you select the Output center frequencies parameter.

Data Types: single | double

Center frequencies of the bandpass filters in Hz, returned as a row vector with number of elements equal to the number of bands.

Dependencies

To enable this port, select the Output center frequencies parameter.

Data Types: single | double

Parameters

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Filter Bank Parameters

Frequency scale used to design the auditory filter bank, specified as mel, bark, or erb.

  • mel –– Design the filter bank as half-overlapped triangles equally spaced on the mel scale.

  • bark –– Design the filter bank as half-overlapped triangles equally spaced on the Bark scale.

  • erb –– Design the filter bank as gammatone filters whose center frequencies are equally spaced on the ERB scale.

Style of the mel scale, specified as oshaughnessy or slaney.

Dependencies

To enable this parameter, set the Frequency scale parameter to mel.

When you select this parameter, the block automatically determines the number of bandpass filters based on the Frequency scale parameter.

  • If you set Frequency scale to mel or bark, then the number of bands is 32.

  • If you set Frequency scale to erb, then the number of bands is equal to ceil(hz2erb(fr(2))-hz2erb(fr(1))), where fr is specified using Frequency range (Hz).

Number of bandpass filters, specified as a positive integer.

Dependencies

To enable this parameter, clear the Auto-determine number of bands parameter.

When you select this parameter, the block sets the Frequency range to [0,fs/2], where fs is the sample rate. The sample rate is determined by the Inherit sample rate from input and Input sample rate (Hz) parameters.

Frequency range in Hz over which to design the auditory filter bank, specified as a two-element row vector.

Dependencies

To enable this parameter, clear the Auto-determine frequency range parameter.

Domain in which the block designs the filter bank, specified as linear or warped. Set the filter bank design domain to linear to design the bandpass filters in the linear (Hz) domain. Set the filter bank design domain to warped to design the bandpass filters in the warped (mel or Bark) domain.

Dependencies

To enable this parameter, set Frequency scale to mel or bark.

Normalization technique used for the filter bank weights, specified as bandwidth, area, or none.

  • bandwidth –– Normalize the weights of each bandpass filter by the corresponding bandwidth of the filter.

  • area –– Normalize the weights of each bandpass filter by the corresponding area of the bandpass filter.

  • none –– The block does not normalize the weights of the filters.

When you select this parameter, the block displays an additional output port, fvec. This port outputs the center frequencies of the bandpass filters.

Open plot to visualize the filters in the frequency domain.

Spectrogram Parameters

Analysis window applied in the time domain, specified as a real vector.

When you select this parameter, the block applies window normalization.

Overlap length of adjacent analysis windows, specified as an integer in the range [0, windowLength), where windowLength is the length of the analysis window, which is specified by Window.

When you select this parameter, the block automatically sets the FFT length to the window length numel(Window).

Number of points used to calculate the DFT, specified as a positive integer.

Dependencies

To enable this parameter, clear the Auto-determine FFT length parameter.

Type of spectrum, specified as magnitude or power.

Number of spectra in the spectrogram, specified as a positive integer.

Number of spectra overlapped across consecutive spectrograms, specified as an integer in the range [0, Number of spectra).

When you select this parameter, the block applies a base 10 logarithm to the spectrogram.

Simulation Parameters

When you select this parameter, the block inherits its sample rate from the input signal. When you clear this parameter, you specify the sample rate in the Input sample rate (Hz) parameter.

Input sample rate in Hz, specified as a real positive scalar.

Dependencies

To enable this parameter, clear the Inherit sample rate from input parameter.

Block Characteristics

Data Types

double | single

Direct Feedthrough

no

Multidimensional Signals

no

Variable-Size Signals

no

Zero-Crossing Detection

no

Extended Capabilities

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Version History

Introduced in R2022a

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See Also

Blocks

Functions

Objects

Topics