melSpectrogram
Mel spectrogram
Syntax
Description
specifies options using one or more name-value arguments.S
= melSpectrogram(audioIn
,fs
,Name=Value
)
melSpectrogram(___)
plots the mel spectrogram on a
surface in the current figure.
Examples
Calculate Mel Spectrogram
Use the default settings to calculate the mel spectrogram for an entire audio file. Print the number of bandpass filters in the filter bank and the number of frames in the mel spectrogram.
[audioIn,fs] = audioread('Counting-16-44p1-mono-15secs.wav'); S = melSpectrogram(audioIn,fs); [numBands,numFrames] = size(S); fprintf("Number of bandpass filters in filterbank: %d\n",numBands)
Number of bandpass filters in filterbank: 32
fprintf("Number of frames in spectrogram: %d\n",numFrames)
Number of frames in spectrogram: 1551
Plot the mel spectrogram.
melSpectrogram(audioIn,fs)
Calculate Mel Spectrums of 2048-Point Windows
Calculate the mel spectrums of 2048-point periodic Hann windows with 1024-point overlap. Convert to the frequency domain using a 4096-point FFT. Pass the frequency-domain representation through 64 half-overlapped triangular bandpass filters that span the range 62.5 Hz to 8 kHz.
[audioIn,fs] = audioread('FunkyDrums-44p1-stereo-25secs.mp3'); S = melSpectrogram(audioIn,fs, ... 'Window',hann(2048,'periodic'), ... 'OverlapLength',1024, ... 'FFTLength',4096, ... 'NumBands',64, ... 'FrequencyRange',[62.5,8e3]);
Call melSpectrogram
again, this time with no output arguments so that you can visualize the mel spectrogram. The input audio is a multichannel signal. If you call melSpectrogram
with a multichannel input and with no output arguments, only the first channel is plotted.
melSpectrogram(audioIn,fs, ... 'Window',hann(2048,'periodic'), ... 'OverlapLength',1024, ... 'FFTLength',4096, ... 'NumBands',64, ... 'FrequencyRange',[62.5,8e3])
Get Filter Bank Center Frequencies and Analysis Window Time Instants
melSpectrogram
applies a frequency-domain filter bank to audio signals that are windowed in time. You can get the center frequencies of the filters and the time instants corresponding to the analysis windows as the second and third output arguments from melSpectrogram
.
Get the mel spectrogram, filter bank center frequencies, and analysis window time instants of a multichannel audio signal. Use the center frequencies and time instants to plot the mel spectrogram for each channel.
[audioIn,fs] = audioread('AudioArray-16-16-4channels-20secs.wav'); [S,cF,t] = melSpectrogram(audioIn,fs); S = 10*log10(S+eps); % Convert to dB for plotting for i = 1:size(S,3) figure(i) surf(t,cF,S(:,:,i),'EdgeColor','none'); xlabel('Time (s)') ylabel('Frequency (Hz)') view([0,90]) title(sprintf('Channel %d',i)) axis([t(1) t(end) cF(1) cF(end)]) end
Input Arguments
audioIn
— Audio input
column vector | matrix
Audio input, specified as a column vector or matrix. If specified as a matrix, the function treats columns as independent audio channels.
Data Types: single
| double
fs
— Input sample rate (Hz)
positive scalar
Input sample rate in Hz, specified as a positive scalar.
Data Types: single
| double
Name-Value Arguments
Specify optional pairs of arguments as
Name1=Value1,...,NameN=ValueN
, where Name
is
the argument name and Value
is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Before R2021a, use commas to separate each name and value, and enclose
Name
in quotes.
Example: FFTLength=1024
Window
— Window applied in time domain
hamming(round(fs*0.03),'periodic')
(default) | vector
Window applied in time domain, specified as a real vector. The number of elements
in the vector must be in the range
[1,size(
]. The number of elements
in the vector must also be greater than audioIn
,1)OverlapLength
.
Data Types: single
| double
OverlapLength
— Analysis window overlap length (samples)
round(0.02*fs
)
(default) | integer in the range [0, (numel(Window
) -
1)]
fs
)Window
) -
1)]Analysis window overlap length in samples, specified as an integer in the range
[0, (numel(
.Window
) - 1)]
Data Types: single
| double
FFTLength
— Number of DFT points
numel(Window
)
(default) | positive integer
Window
)Number of points used to calculate the DFT, specified as a positive integer
greater than or equal to the length of Window
. If unspecified,
FFTLength
defaults to the length of
Window
.
Data Types: single
| double
NumBands
— Number of mel bandpass filters
32
(default) | positive integer
Number of mel bandpass filters, specified as a positive integer.
Data Types: single
| double
FrequencyRange
— Frequency range over which to compute mel spectrogram (Hz)
[0 fs
/2]
(default) | two-element row vector
fs
/2]Frequency range over which to compute the mel spectrogram in Hz, specified as a
two-element row vector of monotonically increasing values in the range [0,
. fs
/2]
Data Types: single
| double
SpectrumType
— Type of mel spectrogram
"power"
(default) | "magnitude"
Type of mel spectrogram, specified as "power"
or
"magnitude"
.
Data Types: char
| string
WindowNormalization
— Apply window normalization
true
(default) | false
Apply window normalization, specified as true
or
false
. When WindowNormalization
is set to
true
, the power (or magnitude) in the mel spectrogram is
normalized to remove the power (or magnitude) of the time domain
Window
.
Data Types: char
| string
FilterBankNormalization
— Type of filter bank normalization
"bandwidth"
(default) | "area"
| "none"
Type of filter bank normalization, specified as "bandwidth"
,
"area"
, or "none"
.
Data Types: char
| string
MelStyle
— Mel style
"oshaughnessy"
(default) | "slaney"
Mel style, specified as "oshaughnessy"
or
"slaney"
.
Data Types: char
| string
ApplyLog
— Apply logarithm
false
(default) | true
Apply base 10 logarithm to the returned mel spectrogram, specified as
true
or false
.
Data Types: logical
Output Arguments
S
— Mel spectrogram
column vector | matrix | 3-D array
Mel spectrogram, returned as a column vector, matrix, or 3-D array. The dimensions
of S
are
L-by-M-by-N, where:
L is the number of frequency bins in each mel spectrum.
NumBands
andfs
determine L.M is the number of frames the audio signal is partitioned into.
size(
, the length ofaudioIn
,1)Window
, andOverlapLength
determine M.N is the number of channels such that N =
size(
.audioIn
,2)
Trailing singleton dimensions are removed from the output
S
.
Data Types: single
| double
F
— Center frequencies of mel bandpass filters (Hz)
row vector
Center frequencies of mel bandpass filters in Hz, returned as a row vector with
length size(
.S
,1)
Data Types: single
| double
T
— Location of each window of audio (s)
row vector
Location of each analysis window of audio in seconds, returned as a row vector
length size(
. The location corresponds to
the center of each window.S
,2)
Data Types: single
| double
Algorithms
The melSpectrogram
function follows the general algorithm to compute
a mel spectrogram as described in [1].
In this algorithm, the audio input is first buffered into frames of
numel(
number of samples. The frames are
overlapped by Window
)OverlapLength
number of samples. The specified
Window
is applied to each frame, and then the frame is converted to
frequency-domain representation with FFTLength
number of points. The
frequency-domain representation can be either magnitude or power, specified by
SpectrumType
. If WindowNormalization
is set to
true
, the spectrum is normalized by the window. Each frame of the
frequency-domain representation passes through a mel filter bank. The spectral values output
from the mel filter bank are summed, and then the channels are concatenated so that each frame
is transformed to a NumBands
-element column vector.
Filter Bank Design
The mel filter bank is designed as half-overlapped triangular filters equally spaced on
the mel scale. NumBands
controls the number of mel bandpass filters.
FrequencyRange
controls the band edges of the first and last filters
in the mel filter bank. FilterBankNormalization
specifies the type of
normalization applied to the individual bands.
The mel scale can be in the O'Shaughnessy style, which follows [2], or the Slaney style, which follows [3].
References
[1] Rabiner, Lawrence R., and Ronald W. Schafer. Theory and Applications of Digital Speech Processing. Upper Saddle River, NJ: Pearson, 2010.
[2] O'Shaughnessy, Douglas. Speech Communication: Human and Machine. Reading, MA: Addison-Wesley Publishing Company, 1987.
[3] Slaney, Malcolm. "Auditory Toolbox: A MATLAB Toolbox for Auditory Modeling Work." Technical Report, Version 2, Interval Research Corporation, 1998.
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
The melSpectrogram
function supports optimized code generation
using single instruction, multiple data (SIMD) instructions. For more information about SIMD
code generation, see Generate SIMD Code from MATLAB Functions for Intel Platforms (MATLAB Coder).
GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
Version History
Introduced in R2019aR2024b: WindowLength
has been removed
The WindowLength
parameter has been removed from the
melSpectrogram
function. Use the Window
parameter instead.
In releases prior to R2020b, you could only specify the length of a time-domain window. The window was always designed as a periodic Hamming window. You can replace instances of the code
S = melSpectrogram(audioin,fs,WindowLength=1024);
S = melSpectrogram(audioIn,fs,Window=hamming(1024,"periodic"));
R2024a: Apply logarithm to mel spectrogram
Set the ApplyLog
name-value argument to true
to
apply a base 10 logarithm to the spectrogram.
R2023b: Support for Slaney-style mel scale
Set the MelStyle
name-value argument to "slaney"
to use the Slaney-style mel scale.
R2023a: Generate optimized C/C++ code for computing mel spectrogram
melSpectrogram
supports optimized C/C++ code generation using
single instruction, multiple data (SIMD) instructions.
R2020b: WindowLength
will be removed in a future release
The WindowLength
parameter will be removed from the
melSpectrogram
function in a future release.
See Also
spectrogram
| mfcc
| gtcc
| mdct
| audioFeatureExtractor
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