Technical Resources
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.
Testing Voice-Controlled & Smartphone Integrated Infotainment Systems
A tutorial and accompanying paper that was presented at the AES Automotive Conference, Sept 11-13, 2019, Neuburg an der Donau, Germany.
Voice-controlled and smartphone integrated vehicle infotainment systems are notoriously complex to test. They have numerous connections from wired to wireless and contain much signal processing, both on the record and on the playback side. This means that their characteristics change according to ‘real world’ conditions of the vehicle’s environment, including cabin acoustics and background noises from road, wind and motors. Furthermore, their multifunctional nature means that there are many aspects of the device that may need to be tested, ranging from voice recognition to music playback and operation as a hands-free telephone. Due to their complex non-linear use cases, these devices often need to be tested at different levels and different environmental conditions.
This tutorial offers practical hands-on advice on how to test such devices, including test configurations, what to measure, the challenges of making open-loop measurements, and how to select a test system.
Prediction of Listener Preference of In-Ear Headphones (Harman Model)
This sequence, inspired by AES papers on statistical models to predict listener preference by Sean E. Olive, Todd Welti, and Omid Khonsaripour of Harman International, applies the Harman target curve for in ear headphones to a measurement made in SoundCheck to yield the predicted user preference for the device under test. The measurements are made in SoundCheck and then saved to an Excel template which performs the necessary calculations to produce a Predicted Preference score using a scale of 0 to 100. The spreadsheet calculates an Error curve which is derived from subtracting the target curve from an average of the headphone left/right response. The standard deviation, slope and average of the Error curve are calculated and used to calculate the predicted preference score.
Microphone SNR Measurement (Background Noise Method)
This sequence characterizes a microphone’s ability to passively and/or actively reject noise in the user’s environment. Unlike traditional microphone SNR measurements which calculate a ratio based upon a reference signal and the microphone’s noise floor, this method utilizes a signal (speech played from a mouth simulator) and noise (background noise played from two or more equalized source speakers) captured by both a reference microphone and the DUT microphone.
First a recording of the baseline ambient noise in the test environment is made and a 1/3 octave RTA spectrum is calculated from the recording. Next, the speech signal (mouth simulator) and noise signals (Left and Right speakers) are played consecutively and recorded separately using the reference microphone. A 1/3 octave RTA spectrum is calculated from each recorded time waveform. Next the same measurements are repeated using the DUT microphone. The resulting RTA spectra are then post processed to produce a signal gain spectrum and a noise gain spectrum which are then used to derive the SNR spectrum of the DUT mic. For best accuracy, the Signal and Noise spectra should be at least 5 dB above the ambient noise floor of the measurement environment.
Triggered Record Using Chirp Trigger and WAV File (Version 17 and later)
This test sequence demonstrates SoundCheck’s Triggered Record – Chirp Trigger function for open loop testing of devices without analog inputs such as smart speakers, wearables, smart home devices, tablets and cellphones. A stimulus WAV file is created in SoundCheck and transferred to the device under test, where it is played back and the response recorded in SoundCheck as if the stimulus were played directly from SoundCheck. The Acquisition step is triggered by the chirp in the stimulus file. Chirp triggers are more robust than level and frequency triggers which are susceptible to false triggering due to background noise.
Measuring Max SPL versus Frequency
This sequence characterizes the performance of transducers such as speakers, microspeakers and headphones by measuring how much voltage is required at each frequency to drive the transducer to specified limits of THD, Rub & Buzz, Perceptual Rub & Buzz or Compression. This is useful for detailed transducer analysis and determination of optimal power rating.
The user selects which metric is tested (one at a time is advised), the limit value and the stimulus start frequency. The sequence then uses an iterative looping process, initially with a +3dB step and then a +0.5dB step to precisely determine the value at which the limit is exceeded. This is repeated across the frequency range to generate curves of voltage and SPL vs frequency at the specified limit.
TIA-920-B Sequence for Measurement of Narrowband and Wideband Digital Phones
This sequence tests to TIA 920-B, a comprehensive US dual-bandwidth standard that applies to both narrowband (NB) and wideband (WB) devices. It also allows a choice between Free Field (FF) and Diffuse Field (DF) as the Listener Reference Point (LRP). The current release of this sequence measures digital communications devices with handset features, according to TIA-920.110-B and speakerphones, according to TIA-920.120-B. Support for headset measurements, according to TIA-920.130-B will be added in a future release.
This module is a large structured set of sequences and subsequences which perform all the measurements. Curves and values are shown on the screen, tolerance checks are performed, and data is saved to Excel spreadsheet files. Completely prompted sequences for calibration of all the transducers are included. After a one-time setup with a sound card and other user-specific interfaces, the sequences are automatic. They run by simply selecting, pressing start, and following prompts where user interaction with the device under test is required. The sequence works with approved sound cards for connection to the transducers. Windows audio devices such as USB headsets work directly with SoundCheck®. VoIP softphones also work with SoundCheck, by means of a recommended third-party Windows audio application.
Triggered Record Using WAV File (Version 16.1 and later)
This sequence allows you to test devices without an analog input such as smart speakers, tablets, cellphones and MP3 players using SoundCheck’s frequency-based trigger functionality. This method offers improved accuracy over previous level-based triggering, especially in noisy environments. A stimulus WAV file is created in SoundCheck, and copied to the device under test, where it is played and the response recorded in SoundCheck as if the stimulus were played directly from SoundCheck. The stimulus WAV file to be used on the device under test (DUT) may be customized in the stimulus step.
Note that this sequence uses the level-based trigger available in SoundCheck 16.1 and later. If you are using version 16.0 or earlier, please see the level-based trigger sequence.
Background Noise Simulation to ETSI ES 202 396-1 Standard
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.
