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 sequence demonstrates a method by which SoundCheck can measure the performance of a loudspeaker embedded in a so-called “smart speaker”. This example assumes that the DUT is an Amazon Echo but it can be adapted for use with virtually any other type of smart speaker by substituting the Echo’s voice activation phrase audio file (“Alexa, play Test Signal One”) with one specific to the desired make and model.
The sequence begins by playing the voice activation phrase out of a source speaker, prompting the DUT to playback the mp3 stimulus file from the cloud, followed by a pause step to account for any activation latency. Following the pause, a triggered record step is used to capture the playback from the DUT. The Recorded Time Waveform is then frequency shifted prior to analysis and the results (Frequency Response, THD and Perceptual Rub & Buzz) are shown on the final display step.
We recommend reading our AES paper on this subject prior to continuing as it contains additional details on the test methods devised for this sequence.
Quantitatively measuring the audio characteristics of IoT (Internet of Things) smart speakers presents several novel challenges. We discuss overcoming the practical challenges of testing such devices and demonstrate how to measure frequency response, distortion, and other common audio characteristics. In order to make these measurements, several measurement techniques and algorithms are presented that allow us to move past the practical difficulties presented by this class of emerging audio devices. We discuss test equipment requirements, selection of test signals and especially overcoming the challenges around injecting and extracting test signals from the device.
Authors: Glenn Hess (Indy Acoustic Research) and Daniel Knighten (Listen, Inc.)
Presented at the 143rd AES Conference, New York 2017
This sequence tests the send and receive performance of a stereo Bluetooth headset with a built-in microphone using a mixture of analog and digital channels. The left and right earphones are measured simultaneously with a stepped sweep from 20 kHz to 20 Hz using two Bluetooth profiles: A2DP and HFP. The mic is measured with a stepped sweep from 8 kHz to 100 Hz using the HFP profile.
A short 1 kHz tone is pre-pended to the test stimulus which serves as reference tone for resampling and frequency shift operations. Post-processing resampling and frequency shift precisely synchronizes the stimulus and response waveforms prior to analysis. In this case, the HarmonicTrak algorithm is used for frequency response and THD analysis. A2DP frequency response and THD curves are displayed on the first display, followed by A2DP & HFP curves superimposed on a subsequent display. Lastly, the Bluetooth headset’s microphone is tested with HFP and its frequency response is shown on the final display along with the previously collected data.
This sequence tests a stereo headphone connected to a portable audio device such as a mobile phone or MP3 player. It is particularly useful for testing headphones with proprietary connectors such as the Lightning connector which otherwise can’t be tested in a conventional “closed loop” test configuration.
The test stimulus is created in SoundCheck, saved as a WAV file and loaded on to the portable device for playback. Both left and right earphones are measured simultaneously using a continuous log sweep from 20 Hz to 20 kHz. The sequence uses a short 1 kHz tone, pre-pended to the normal test stimulus to automatically trigger the test when playback of the test signal begins; it also serves as reference tone for any frequency shift calculations. Post-processing precisely synchronizes the stimulus and response waveforms, and then calculation of the measurement parameters proceeds as with any conventional headphone. In this case, analysis is performed using the Time Selective Response (TSR) algorithm which performs THD and fundamental frequency response analysis simultaneously in addition to producing an impulse response. The fundamentals are then post processed to derive the sensitivity of the left and right channels at 1 kHz.
In order to minimize costly warranty repairs, automotive manufacturers 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 automotive manufacturers to work with automotive loudspeaker suppliers to define reasonable specifications and tolerances, and to understand both how the loudspeaker manufacturers are testing and also how to implement their own measurements for incoming QC purposes.
Specifying and testing automotive loudspeakers can be tricky since loudspeakers are inherently nonlinear, time variant and affected by their working conditions & environment which can be change dramatically and rapidly in a vehicle. This paper examines the loudspeaker characteristics that can be measured, and discusses common pitfalls and how to avoid them on a loudspeaker production line. Several different audio test methods and measurements for end-of-the-line automotive speaker quality control are evaluated, and the most relevant ones identified. Speed, statistics, and full traceability are also discussed.
Authors: Steve Temme, Listen, Inc. and Viktor Dobos, Harman/Becker Automotive Systems Kft.
Presented at the 142nd AES Convention, Berlin, Germany
This SoundCheck ONE template sequence contains all the essential steps for basic headphone measurements using SoundCheck ONE and AudioConnectTM. The sequence can be easily customized and saved for specific products by turning individual measurements on and off, and by adjusting settings within each sequence step such as stimulus range and level, tolerance limits, graphical displays, and data saving.
Please note that sequences in SoundCheck ONE cannot have steps added/removed or the layout modified – the full version of SoundCheck is required for this capability.
As in-vehicle audio system output level increases, so too does audio distortion. At what level is distortion audible and how is sound quality perceived as level increases? Binaural recordings of musical excerpts played through the in-vehicle audio system at various volume levels were made in the driver’s position. These were adjusted to equal loudness and played through a low distortion reference headphone. Listeners ranked both distortion audibility and perceived sound quality. The distortion at each volume level was also measured objectively using a commercial audio test system. The correlation between perceived sound quality and objective distortion measurements is discussed.
Authors: Steve Temme, Listen, Inc. and Patrick Dennis, Nissan Technical Center North America, Inc.,
Presented at the 141st AES Convention, Los Angeles, CA 2015
This sequence demonstrates the two most common microphone measurements, frequency response and sensitivity, on a microphone embedded in a recording device. Typically when measuring a microphone the response of the device can be captured simultaneously with the stimulus. However, with devices such as voice recorders and wireless telephones forming a closed loop can be cumbersome or impossible. This sequence demonstrates how to measure such a device by recording the signal on the device under test, transferring that recording to the computer running SoundCheck and then using a Recall step to import the recorded waveform and analyze it.
Note that this specific sequence, v3, is an improvement on the prior versions. The v1 release required that the audio file containing the recorded response waveform be manually windowed outside of SoundCheck before being analyzed. The v2 release utilized a new feature in SoundCheck 14, using values from the memory list to semi-automatically trim the waveform before analysis. This v3 release completely automates waveform editing.