Python Co-Execution for AI Speech Command Recognition
다운로드 수: 109
업데이트 날짜: 2021/8/25
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.
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.
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 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™.
The license is available in the License file in this repository.
MathWorks Audio Toolbox Team (2023). Python Co-Execution for AI Speech Command Recognition (https://github.com/matlab-deep-learning/coexecution_speech_command/releases/tag/v1.0), GitHub. 검색됨 .