Code Generation and Deployment

Generate standalone applications for desktop computers, mobile devices, and embedded targets

After you develop your application using Audio Toolbox™, features, you can generate portable C/C++ source code, standalone executables, or standalone applications from your MATLAB® code or Simulink® model. With code generation, you can:

  • Run your algorithm on machines that do not have MATLAB or Simulink installed.

  • Speed up processing while you work in the MATLAB or Simulink environment.

  • Embed your algorithm in hardware.

  • Incorporate your algorithms into legacy code.

This table compares deployment characteristics of MATLAB Compiler™ and MATLAB Coder™ functionality. Use this table to decide how to deploy your MATLAB code or Simulink model.

Deployment CharacteristicUsing MATLAB Compiler FunctionalityUsing MATLAB Coder Functionality
OutputNonreadable shared libraries.Portable and readable C source code.
Library dependencyMATLAB Runtime.

Library dependency only for audio I/O features: Run Audio I/O Features Outside MATLAB and Simulink.

Supported platforms for deployment

Windows®, Mac, and Linux®.

Any platform that supports ANSI®/ISO® C/C++ code.

Intellectual property protection

Packaged code is encrypted.

Code is not encrypted. You can protect your IP by generating shared libraries instead of readable code.

Algorithm acceleration

Same speed as MATLAB.

Potentially faster, depending on the algorithm.

MATLAB graphicsSupported.Not supported.

To deploy an audio plugin to a digital audio workstation, see Export a MATLAB Plugin to a DAW.

To deploy a System object™ audio plugin to Simulink, see Convert Audio Plugin System Objects to Simulink Blocks.

Topics

What is C Code Generation from MATLAB?

Introduces code generation support.

Run Audio I/O Features Outside MATLAB and Simulink

Set your system environment to use dynamic library files for deployed audio I/O System objects and blocks.

Related Information

Featured Examples

Speech Command Recognition Code Generation on Raspberry Pi

Speech Command Recognition Code Generation on Raspberry Pi

Deploy feature extraction and a convolutional neural network (CNN) for speech command recognition to Raspberry Pi™. To generate the feature extraction and network code, you use MATLAB Coder, MATLAB Support Package for Raspberry Pi Hardware, and the ARM® Compute Library. In this example, the generated code is an executable on your Raspberry Pi, which is called by a MATLAB script that displays the predicted speech command along with the signal and auditory spectrogram. Interaction between the MATLAB script and the executable on your Raspberry Pi is handled using the user datagram protocol (UDP). For details about audio preprocessing and network training, see Speech Command Recognition Using Deep Learning.

Open Live Script
Speech Command Recognition Code Generation with Intel MKL-DNN

Speech Command Recognition Code Generation with Intel MKL-DNN

Deploy feature extraction and a convolutional neural network (CNN) for speech command recognition on Intel® processors. To generate the feature extraction and network code, you use MATLAB Coder and the Intel Math Kernel Library for Deep Neural Networks (MKL-DNN). In this example, the generated code is a MATLAB executable (MEX) function, which is called by a MATLAB script that displays the predicted speech command along with the time domain signal and auditory spectrogram. For details about audio preprocessing and network training, see Speech Command Recognition Using Deep Learning.

Open Live Script
Parametric Audio Equalizer for Android Devices

Parametric Audio Equalizer for Android Devices

Use the Parametric EQ block and the multibandParametricEQ System object™ from the Audio Toolbox™ to implement a parametric audio equalizer model. You can run the model on your host computer or deploy it to an Android device.

Open Script
Parametric Audio Equalizer for iOS Devices

Parametric Audio Equalizer for iOS Devices

Use the Parametric EQ block and the multibandParametricEQ System object™ to implement a parametric audio equalizer model, that can run on your host computer or an Apple iOS device.

Open Script
Audio Effects for iOS Devices

Audio Effects for iOS Devices

Use System objects™ from Audio Toolbox™ to implement echo and reverberation effects in a Simulink® model. You can run the model on your host computer or deploy it to an Apple iOS device.

Open Model
Multiband Dynamic Range Compression for iOS Devices

Multiband Dynamic Range Compression for iOS Devices

Use the Crossover Filter block and compressor System object™ from the Audio Toolbox™ to implement a multiband dynamic range compressor model. You can run the model on your host computer or deploy it to an Apple iOS device.

Open Model
Generate Standalone Executable for Parametric Audio Equalizer

Generate Standalone Executable for Parametric Audio Equalizer

Generate a standalone executable for parametric equalization using MATLAB Coder™ and use it on an audio file. multibandParametricEQ is used for the equalization algorithm. The example allows you to dynamically adjust the coefficients of the filters using a user interface (UI) that is running in MATLAB.

Open Script
Deploy Audio Applications with MATLAB Compiler

Deploy Audio Applications with MATLAB Compiler

Use MATLAB Compiler™ to create a standalone application from a MATLAB function. The function implements an audio processing algorithm and plays the result through your audio output device.

Open Script
Desktop Real-Time Audio Acceleration with MATLAB Coder

Desktop Real-Time Audio Acceleration with MATLAB Coder

Accelerate a real-time audio application using C code generation with MATLAB Coder.

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Audio Toolbox Documentation

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