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Cepstral Coefficients

Extract cepstral coefficients from spectrogram

Since R2022b

  • Cepstral Coefficients block

Libraries:
Audio Toolbox / Features

Description

The Cepstral Coefficients block extracts the cepstral coefficients from a real-valued spectrogram or auditory spectrogram. Cepstral coefficients are commonly used as compact representations of audio signals.

Ports

Input

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Spectrogram or auditory spectrogram, specified as an L-by-M matrix or L-by-M-by-N array, where:

  • L is the number of frequency bands.

  • M is the number of frames.

  • N is the number of channels.

Data Types: single | double

Output

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Cepstral coefficients, returned as an M-by-B matrix or M-by-B-by-N array, where:

  • M is the number of frames in the input spectrogram.

  • B is the number of coefficients returned per frame, which is specified by the Number of cepstral coefficients parameter.

  • N is the number of channels in the input spectrogram.

Data Types: single | double

Parameters

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Number of cepstral coefficients, specified as a positive integer greater than 1.

Type of nonlinear rectification applied to the spectrum prior to the discrete cosine transform, specified as Logarithm, Cubic root, or None.

  • Interpreted execution –– Simulate model using the MATLAB® interpreter. This option shortens startup time but has a slower simulation speed than Code generation. In this mode, you can debug the source code of the block.

  • Code generation –– Simulate model using generated C code. The first time you run a simulation, Simulink generates C code for the block. The C code is reused for subsequent simulations, as long as the model does not change. This option requires additional startup time, but the speed of the subsequent simulations is comparable to Interpreted execution.

Block Characteristics

Data Types

double | single

Direct Feedthrough

no

Multidimensional Signals

no

Variable-Size Signals

no

Zero-Crossing Detection

no

Algorithms

Given an auditory spectrogram, the algorithm to extract N cepstral coefficients from each individual spectrum comprises the following steps.

  1. Rectify the spectrum by applying a logarithm, cubic root, or optionally perform no rectification.

  2. Apply the discrete cosine transform (DCT-II) to the rectified spectrum.

  3. Return the first N coefficients from the cepstral representation.

For more information, see [1].

References

[1] Rabiner, Lawrence R., and Ronald W. Schafer. Theory and Applications of Digital Speech Processing. Upper Saddle River, NJ: Pearson, 2010.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Version History

Introduced in R2022b