Python Co-Execution for AI Speech Command Recognition

PyTorch and TensorFlow Co-Execution for Speech Command Recognition
Updated 25 Aug 2021

PyTorch and TensorFlow Co-Execution for Training a Speech Command Recognition System

This repo provides examples of co-executing MATLAB® with TensorFlow and PyTorch to train a speech command recognition system.

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Signal processing engineers that use Python to design and train deep learning models are still likely to find MATLAB® useful for tasks such as dataset curation, signal pre-processing, data synthesis, data augmentation, and feature extraction. Open-source alternatives exist for those tasks and they could be OK to use when replicating a pre-existing model or training recipe. However, for original technical development work, most users find those tasks easier in MATLAB®.

Creator: MathWorks® Development


To accelerate training, a GPU and the following toolbox is recommended:

This repo includes two co-execution examples, with additional requirements.



Get Started

See SetupNotes.mlx for setup instructions for both examples included with this repo.

There are two high-level examples in this repo.

Call MATLAB from Python

CallMATLABFromPythonPytorch.mlx - In this example, Python™ is your main environment. You call into MATLAB® to perform dataset management and audio feature extraction.

Call MATLAB from Python image

Call Python from MATLAB

CallPythonTensorFlowFromMATLAB.mlx - In this example, MATLAB® is your main environment. The dataset management, audio feature extraction, training loop, and evaluation happen in MATLAB®. The deep learning network is defined and executed in Python™.

Call Python from MATLAB image


The license is available in the License file in this repository.

Cite As

MathWorks Audio Toolbox Team (2024). Python Co-Execution for AI Speech Command Recognition (, GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2021a
Compatible with R2021a and later releases
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.