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.
Read audio from a file and write audio to speakers.
Create an audio test bench and apply real-time processing.
Create a model using the Simulink® templates and blocks for audio processing.
Train, validate, and test a simple long short-term memory (LSTM) to classify sounds.
Use transfer learning to retrain YAMNet, a pretrained convolutional neural network (CNN), to classify a new set of audio signals.
Create a simple audio plugin in MATLAB and then use it to generate a VST plugin.
Learn about the role of digital audio workstations (DAWs), audio plugins, and Musical Instrument Digital Interface (MIDI) controllers in designing audio processing algorithms.
Learn common tools and workflows to apply deep learning to audio applications.
What Is Audio Toolbox?
Design and test audio processing systems with Audio Toolbox.
Introduction to Deep Learning for Audio and Speech
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.