Getting Started with Audio Toolbox

Design and analyze speech, acoustic, and audio processing systems

Audio Toolbox™ provides tools for audio processing, speech analysis, and acoustic measurement. It includes algorithms for audio signal processing (such as equalization and dynamic range control) and acoustic measurement (such as impulse response estimation, octave filtering, and perceptual weighting). It also provides algorithms for audio and speech feature extraction (such as MFCC and pitch) and audio signal transformation (such as gammatone filter bank and Mel-spaced spectrogram).

Toolbox apps support live algorithm testing, impulse response measurement, and audio signal labeling. The toolbox provides streaming interfaces to ASIO™, WASAPI, ALSA, and CoreAudio sound cards and MIDI devices, and tools for generating and hosting standard audio plugins such as VST and Audio Units.

With Audio Toolbox you can import, label, and augment audio data sets, as well as extract features and transform signals for machine learning and deep learning. You can prototype audio processing algorithms in real time by streaming low-latency audio while tuning parameters and visualizing signals. You can also validate your algorithm by turning it into an audio plugin to run in external host applications such as Digital Audio Workstations. Plugin hosting lets you use external audio plugins like regular objects to process MATLAB® arrays. Sound card connectivity enables you to run custom measurements on real-world audio signals and acoustic systems.

Installation and Configuration

Tutorials

About Audio Plugins

About Deep Learning and Machine Learning for Audio

Featured Examples

Videos

What Is Audio Toolbox?
Design and test audio processing systems with Audio Toolbox.

Introduction to Deep Learning for Audio and Speech Applications
Create or ingest datasets, extract features, and develop audio and speech analytics using Statistics and Machine Learning Toolbox, Deep Learning Toolbox, or other machine learning tools.