This sequence calibrates a reference speaker by automatically adjusting its response against a target curve, eliminating the need to step through the calibration editor. It runs using the “Reference Mic” input and “Source Speaker.dat” output device, providing fast and consistent calibration with a single sequence run. To use different signal paths or devices, the calibration editor and sequence must be updated with matching names.
This sequence finds the test level (volts) to achieve a desired sound pressure level (dB SPL). The user enters the desired sound pressure level. 1 volt is played through the amplifier which is used to then calculate the appropriate voltage level to obtain the desired Sound pressure level. The sequence then runs a stepped sine sweep using the calculated voltage level and outputs the frequency response.
The purpose of this sequence is to compare the response of an artificial mouth when face masks of different construction are mounted on the mouth. The sequence assumes a lightweight disposable mask and a heavy multi-layer cloth mask. A stepped sinewave from 10 kHz – 100 Hz is played from the unoccluded mouth and the operator is then prompted to mount and measure the two masks over the mouth. The three mouth responses are then displayed on one x-y graph and the difference curves (unoccluded mouth vs masked mouth) are displayed on another. Finally, the average attenuation created by each mask across the measurement range is displayed on a table.
Note that the curve names are constructed by selecting the “Use Input Data Name” option on the Curves tab of the Analysis editors. The appended text in parentheses (No Mask, Disposable Mask, Cloth Mask) comes from the custom naming of the three Recorded Time Waveforms so if you wish to edit these, it can be done by editing the Waveform names in the Acquisition steps.
This sequence demonstrates how SoundCheck’s Windowing post-processing function is applied to waveforms to remove measurement artifacts that might otherwise create false auto delay values and subsequent analysis errors.
This sequence uses data from a customer who was measuring the directivity of a hearing aid-type device by mounting it on a rotating HATS and using a short duration log sweep. The DUT does not have a perfect seal in the HATS ear and the devices signal processing produces a latency of around 35ms. When viewing the Recorded Time waveforms, both the leakage signal and the amplified signal can be seen. As the DUT approaches 180° the magnitude of the leakage into the HATS ear exceeds that of the amplified signal, creating false Record Delay values and subsequent analysis errors. This sequence applies a window to the Recorded Time Waveform to remove the early-arrival leakage, and calculates the true Record Delay values of the amplified signal, obtaining consistent analysis results at all angles of rotation. This sequence can be adapted to your other requirements, for example, removing early arrival signals from a waveform or editing out excessive delay in a waveform.
TCP/IP control of SoundCheck provides a powerful and expandable command format for controlling and interacting with SoundCheck via any programming language (C#, C++, MATLAB, VB.net, LabVIEW, Python, etc.), on any operating system, either locally or through a network. This is valuable for anyone wishing to control SoundCheck from an external program, e.g. as part of an overall test plan or for factory automation. Using this feature, a single computer can control multiple SoundCheck systems, simplifying production line measurements.
The ability to connect to, and control SoundCheck via TCP/IP first appeared in SoundCheck over 3 years ago, but for version 18, it has been enhanced with the ability to pass test configuration data into the memory list from external programs. This means, for example, that by externally storing parameters such as limits, test levels, and test signals, a single sequence can be used for multiple products, or testing the same product multiple times, simplifying sequence maintenance, and reducing test configuration time.
This application note and accompanying demo scripts walk you through how to use Python to:
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.
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.
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.
Listen is a global leader in audio measurement and analysis, with over 30 years’ experience developing innovative test methods and algorithms. SoundCheck, our powerful software-based audio analyzer, pairs with our test interfaces, precision microphones, and accessories to offer a complete solution for testing loudspeakers, headphones, microphones, smart devices, communication systems, hearing aids, automotive audio, and more. Trusted by engineers worldwide, Listen delivers the accuracy and flexibility essential for modern audio testing, from the R&D lab to the production line.
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