Combine Optimization Toolbox™ and Audio Toolbox to develop an algorithm that automatically tunes a set of filter parameters.

Model a smart speaker system in Simulink that incorporates voice command recognition and operates in real time.

Use a multistage/multirate approach to sample rate conversion between different audio sampling rates.

Design parametric equalizer filters. Parametric equalizers are digital filters used in audio for adjusting the frequency content of a sound signal. Parametric equalizers provide capabilities beyond those of graphic equalizers by allowing the adjustment of gain, center frequency, and bandwidth of each filter. In contrast, graphic equalizers only allow for the adjustment of the gain of each filter.

Demonstrates two forms of graphic equalizers constructed using building blocks from Audio Toolbox™. It also shows how to export them as VST plugins to be used in a Digital Audio Workstation (DAW).

Simulate a digital audio multiband dynamic range compression system.

Design and use three audio effects that are based on varying delay: echo, chorus and flanger. The example also shows how the algorithms, developed in MATLAB, can be easily ported to Simulink.

An audio plugin designed to enhance the perceived sound level in the lower part of the audible spectrum.

Implement a real-time audio "phaser" effect which can be tuned by a user interface (UI). It also shows how to generate a VST plugin for the phaser that you can import into a Digital Audio Workstation (DAW).

Extract an audio source from a stereo mix based on its panning coefficient. This example illustrates MATLAB® and Simulink® implementations.

Apply adaptive filters to acoustic echo cancellation (AEC).

Use the Least Mean Square (LMS) algorithm to subtract noise from an input signal. The LMS adaptive filter uses the reference signal on the Input port and the desired signal on the Desired port to automatically match the filter response. As it converges to the correct filter model, the filtered noise is subtracted and the error signal should contain only the original signal.

Apply adaptive filters to the attenuation of acoustic noise via active noise control.

Implement a phase vocoder to time stretch and pitch scale an audio signal.

Use a phase vocoder to implement time dilation and pitch shifting of an audio signal.

Remove a 250 Hz interfering tone from a streaming audio signal using a notch filter.

Implement a Vorbis decoder, which is a freeware, open-source alternative to the MP3 standard. This audio decoding format supports the segmentation of encoded data into small packets for network transmission.

Apply reverberation to audio by using the Freeverb reverberation algorithm. The reverberation can be tuned using a user interface (UI) in MATLAB or through a MIDI controller. This example illustrates MATLAB® and Simulink® implementations.

Simulate the design of a cochlear implant that can be placed in the inner ear of a profoundly deaf person to restore partial hearing. Signal processing is used in cochlear implants to convert sound to electrical pulses. The pulses can bypass the damaged parts of a deaf person's ear and be transmitted to the brain to provide partial hearing.

Compress the dynamic range of a signal by modifying the range of the magnitude at each frequency bin. This nonlinear spectral modification is followed by an overlap-add FFT algorithm for reconstruction. This system might be used as a speech enhancement system for the hearing impaired. The algorithm in this simulation is derived from a patented system for adaptive processing of telephone voice signals for the hearing impaired originally developed by Alvin M. Terry and Thomas P. Krauss at US West Advanced Technologies Inc., US patent number 5,388,185.