Apply deep learning to audio and speech processing applications by using Deep Learning Toolbox™ together with Audio Toolbox™.
|Audio Labeler||Define and visualize ground-truth labels|
|Datastore for collection of audio files|
Introduction to Deep Learning for Audio Applications (Audio Toolbox)
Learn common tools and workflows to apply deep learning to audio applications.
Classify Sound Using Deep Learning (Audio Toolbox)
Train, validate, and test a simple long short-term memory (LSTM) to classify sounds.
This example shows how to train a simple deep learning model that detects the presence of speech commands in audio.
This example shows how to denoise speech signals using deep learning networks.
This example shows how to classify the gender of a speaker using deep learning.
This example shows how to detect regions of speech in a low signal-to-noise environment using deep learning.
This example shows how to classify spoken digits using wavelet time scattering paired with a support vector machine and a deep convolutional network based on mel-frequency spectrograms.
This example shows how to isolate a speech signal using a deep learning network.
This example shows a typical workflow for feature selection applied to the task of speech emotion recognition.
This example shows how to identify a keyword in noisy speech using a deep learning network.
This example shows how to create a multi-model late fusion system for acoustic scene recognition.