With over 100 combined years of audio measurement experience, our team has created a wealth of technical papers, sequences, articles and other useful information to assist you with your audio test needs. Please browse the collection below, or filter by type of resource.
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This Background Noise Simulation sequence follows the ETSI ES 202 396-1 standard. It will automatically calibrate a standardized 4.1 speaker / subwoofer setup in accordance to the ETSI ES 202 396-1 standard “Loudspeaker Setup for Background Noise Simulation” and provide an equalized, calibrated playback solution to stress your device in a standardized and repeatable way.
Included with the sequence is a library of real world binaural recordings from the ETSI standard: cafeteria, pub, crossroad, vehicle, single voice distractor, and office noises. Custom or user-defined binaural recordings can also be used to create background noise tests directly applicable to your product. This sequence has many applications including evaluating ANC on headphones, noise suppression on communication devices, voice recognition testing of smart speakers / IoT, SNR optimization of microphones on telepresence devices and beamforming directionality studies of microphone arrays.
This sequence allows you to measure a playback system without analog inputs using a 6 microphone array. Specifically, the sequence is designed to measure an in-car audio system. A stimulus WAV file is created in SoundCheck and transferred to the device under test (DUT) where it is played back and the response captured by SoundCheck using a triggered record function. The 6 recordings are batch analyzed to produce individual fundamental curves and the curves are post-processed to produce a single average curve from which an average sensitivity value is calculated.
In this paper, a mathematical definition of Total Harmonic Distortion + Noise suitable for testing high-resolution digital audio systems is presented. This formal definition of the “distortion analyzer” mentioned in AES17 defines THD+N as the RMS error of fitting a sinusoid to a noisy and distorted sequence of measurements. We present the key theoretical result that under realistic conditions a modern THD+N analyzer is well-described by a Normal probability distribution with a simple relationship between relative error and analysis dwell time. These findings are illustrated by comparing the output of a commercial distortion analyzer to our proposed method using Monte Carlo simulations of noisy signal channels. We will demonstrate that the bias of a well-designed distortion analyzer is negligible.
Authors: Steve Alfred B. Roney The Mathworks, Inc. (formerly Listen, Inc.) Steve Temme, Listen, Inc.
Presented at AES 2018, New York, NY.
In order to minimize costly warranty repairs, loudspeaker OEMS impose tight specifications and a “total quality” requirement on their part suppliers. At the same time, they also require low prices. This makes it important for driver manufacturers and contract manufacturers to work with their OEM customers to define reasonable specifications and tolerances. They must understand both how the loudspeaker OEMS are testing as part of their incoming QC and also how to implement their own end-of-line measurements to ensure correlation between the two.
Authors: Steve Temme, Listen, Inc. and Viktor Dobos, Harman/Becker Automotive Systems Kft.
Presented at ISEAT 2017, Shenzhen, China
Author: Shannon Becker. Reprinted from the March 2018 issue of Audio Xpress.
Shannon Becker interviews Steve Temme about how he founded Listen, Inc. and grew it from a start-up into an audio measurement leader.
Author: Daniel Knighten. Reprinted from the July 2017 issue of Voice Coil.
In this article, Dan Knighten discusses how to overcome the challenges of measuring headphones with wireless and digital interfaces such as Bluetooth, Lightning and USB-C to make the same measurements as on conventional wired headphones.
Author: Daniel Knighten (Listen, Inc) and Glenn Hess (Indy Acoustic Research). Reprinted from the March 2018 issue of Audio Xpress.
In this article, we describe techniques to characterize the frequency response, output level, and distortion of the device under test to enable direct comparisons between Internet of Things (IoT) smart speakers and conventional speakers.
Authors: Zarina Bhimani, Steve F. Temme (Listen, Inc.), Patrick Dennis (Nissan Motor Co.). Reprinted from the 2017 Loudspeaker Industry Sourcebook.
Steve Temme and Patrick Dennis discuss their research exploring test methods that will help determine audible distortion and enable manufacturers to test sound equipment after it is installed