Standardized measurement of in-car audio systems remains an ongoing challenge, particularly regarding microphone configuration and placement, test signals, and correlation with perception. Current recommendations from the AES Technical Committee on Automotive Audio (TC-AA) advocate spatial averaging using multi-microphone arrays to improve repeatability.
While this method reduces the influence of reflections and standing waves to improve frequency magnitude measurement consistency and repeatability, it limits frequency, phase and amplitude resolution, which help identify the root causes of the distortions and evaluate their perceptual impact. An alternative approach is to apply frequency-normalized distortion analysis, where reflections or standing waves in the frequency response are also echoed in the distortion results, and greatly reduced by direct comparison of the two measurements. In this paper, spatial averaged distortion measurements using the TC-AA recommended 6 microphone array are compared with normalized distortion calculations, and a single microphone capture using the normalized distortion method.
Buzz, Squeak & Rattle (BSR) measurements otherwise known as Rub & Buzz or Impulsive Distortion measurements are also challenging. The TC-AA recommends a crest factor algorithm, available in a few audio measurement systems. This adequately detects transient distortions, but is susceptible to background noise, therefore requires a tightly controlled environment for making measurements. Two other methods, enhanced perceptual Rub & Buzz and enhanced Loose Particles offer improved repeatability in the presence of background noise, and the results are easier to correlate to audibility. The three methods are compared, both in a quiet environment, and with background noise.
Author: Steve Temme, Listen, Inc. Presented at the AES Automotive Conference (July 2026) Detroit, Michigan
This paper investigates improved methods for measuring audible distortion in automotive infotainment systems. Traditional Total Harmonic Distortion (THD) measurements are often compromised by vehicle cabin reflections and standing waves, making it difficult to distinguish genuine loudspeaker distortion from acoustic artifacts. The paper demonstrates that Frequency-Normalized Total Harmonic Distortion (nTHD) produces more accurate and perceptually meaningful results than conventional THD, while also reducing measurement complexity and cost.
Key Findings
Frequency-normalized THD (nTHD) largely removes the effects of cabin reflections by comparing harmonics with the fundamental at the same measured frequency before calculating distortion.
nTHD produces clearer distortion measurements than conventional THD and more accurately identifies the true source of distortion.
A single microphone using nTHD closely matches measurements obtained from the AES TC-AA recommended six-microphone array, suggesting a practical lower-cost solution for production-line testing.
For Buzz, Squeak and Rattle (BSR) measurements, traditional Crest Factor analysis is susceptible to background noise.
Two alternative techniques—Enhanced Perceptual Rub & Buzz (ePRB) and Enhanced Loose Particles (eLP)—provide better repeatability, improved noise immunity, and stronger correlation with what listeners actually hear.
Why It Matters
Automotive audio systems are measured in highly reflective environments where conventional distortion measurements can misinterpret reflections as loudspeaker defects. Frequency-normalized distortion separates linear acoustic effects from true nonlinear distortion, allowing engineers to identify problems more accurately. The paper also shows that perceptually based distortion measurements better reflect human hearing and remain reliable in noisy environments such as vehicle production facilities.
Applications
The techniques described are particularly valuable for:
Automotive infotainment system development
End-of-line manufacturing testing
Loudspeaker quality assurance
Diagnosis of Buzz, Squeak and Rattle (BSR)
Production environments requiring faster, lower-cost acoustic measurements
Conclusion
The paper concludes that frequency-normalized THD provides a more accurate representation of audible distortion than conventional THD in vehicle cabins. Combined with perceptually based Rub & Buzz and Loose Particle measurements, it offers improved correlation with listener perception, greater immunity to background noise, and the potential to replace expensive multi-microphone measurement systems with a single microphone for many automotive production applications.
https://www.listeninc.com/wp/media/2026/07/Paper_AES_Automotive.png776598Renee Lucashttps://www.listeninc.com/wp/media/logo.pngRenee Lucas2026-07-31 09:07:412026-08-13 15:53:25Overcoming Challenges of Measuring Distortion Audibility in Automotive Audio Systems
How do you measure hearing protection devices? In this short video, we demonstrate how to measure hearing protection using SoundCheck in accordance with the ANSI S3.19-1974 standard. You’ll see how to set up a head and torso simulator, calibrate the system, and perform repeated unoccluded and occluded measurements using pink noise to accurately calculate attenuation and Noise Reduction Rating (NRR). This method can be used for a wide range of hearing protection devices to ensure reliable and standardized performance testing.
Watch this Video Demo of Measuring Hearing Protection
Video Transcript: How to Measure Hearing Protection
In this short video, we’ll measure the performance of hearing protection devices and calculate the Noise Reduction Rating using the ANSI S3.19-standard.
Our setup is simple. We have a head and torso simulator to wear the hearing protectors and capture the signal, a speaker to play the test stimulus, and a calibrated reference microphone for speaker calibration. The stimulus and response signals are transmitted to and from the computer using the AmpConnect 621 audio interface which also contains an amplifier to power the speaker. I also have a SoundConnect 2 to provide 200V polarization voltage to the ears since I’m using an older HATS.The newer versions have pre-polarized ear simulators so they can be powered directly from Listen’s audio interfaces.
We’ll play a pink noise test signal and capture the response with the ears unoccluded. We’ll then put on the hearing protectors and make the occluded measurement. We’ll re-position and re-measure several times and take an average to account for fit variations. We’ll then compare the occluded and unoccluded data to calculate the noise reduction ratio, or NRR.
My reference microphone is already calibrated, and connected to input 1. Now I need to calibrate the ear simulator input signal paths and source speaker in the calibration editor.
Let’s go to Setup > Calibration and go to Input Signal paths > Ear Sim L. I have connected this to Input 2, now I’m ready to calibrate the ear. I’m going to use a B&K 4231 calibrator with the coupler UA 1546, hit the calibrate button and save the sensitivity value. Now we’ll repeat that for the other ear, Ear Sim R which is connected to Input 3..
Next, I need to calibrate the source speaker. I’ll place the reference mic as close to one side of the hearing protector test fixture as possible. We’ll navigate to the output signal paths tab inside the Calibration editor, and select Source speaker. I’ll make sure it is assigned to Output 3 because that’s the amplifier output of the AmpConnect 621 where we have it connected. Now I’ll click Calibrate using Reference mic as the input. We’ll use a level of 80dBSPL from 10kHz-100Hz, the same frequency range that we’ll use in the sequence. It’s not quite flat, so we’ll iterate a couple more times until the EQ’d response is flat. This looks good. Now, everything is calibrated, we’re ready to run the sequence.
Let’s hit start.
First, the sequence wants to know how many trials I want to do. We’re going to make this measurement several times, removing the DUT and placing it back so that we can average the response to account for fit variation. We’ll run it 5 times for the purposes of this demo.
First, we’ll capture the unoccluded response – this means measuring the sound levels without any hearing protection in place. The test sequence will play pink noise through the speaker and record the sound spectrum at both ears of the fixture. Let’s hit enter.
Let’s save this measurement.
Now the sequence is asking me to place the hearing protection device onto the test fixture and we’ll continue to repeat the test to measure the occluded response. Now we’ll just follow the instructions and do it four more times.
Next, the sequence performs postprocessing steps on these unoccluded and occluded measurements to calculate the attenuation at different frequencies, average attenuation, standard deviation and finally the Noise Reduction Rating (NRR) – you can see its 26.6 on the left and 32.1 on the right. These measurements provide a complete picture of the device’s performance.
And that’s it! Using this pre-written sequence – which you can download from our website – it’s quick and easy to accurately measure attenuation and determine the Noise Reduction Rating of any hearing protection device to the ANSI standard.
Download the distortion measurement tutorial presented April 30th at the AES Bay Area Chapter Meeting.
In this presentation, Steve Temme approaches distortion from a psychoacoustic perspective, explaining how we perceive it, why traditional metrics can fall short, and how methods like Normalized THD better align with human hearing. He also examines the trade-offs introduced by active noise cancellation, demonstrating how reducing one type of distortion can unintentionally impact perceived sound quality.
Download the distortion measurement tutorial presented May 28, 2026 at AES Copenhagen.
In this tutorial, Steve Temme explains the challenges of measuring distortion including the convolution of linear and non-linear distortion, the variation in measured distortion with signal and level, and the challenges of correlating different types of distortion measurement. He discusses metrics for measuring with sinusoidal tones such as THD, THD+N and IMD, as well as with real-world signals such as speech, music and noise, and shares the latest developments in perceptual measurements designed for easy comparison with audibility. The tutorial was presented on Thurs, May 28th at the 2026 AES European Conference in Copenhagen, DK.
Get up and running with your AmpConnect 621 and SoundCheck in minutes! This step-by-step guide walks through installation, activating your license, hardware setup, and running a self-test to ensure everything is working correctly. We’ll also walk through a quick loudspeaker measurement so you can start testing right away!
Video Transcript: Installation Guide: AmpConnect 621 + SoundCheck
Hi, I’m Jason from Listen. Today I’m going to show you how to install and configure your new AmpConnect 621 with SoundCheck. Before you start, make sure you have:
Your hardware key
Your AmpConnect 621 and the USB cable to connect it to the computer.
Access to the internet to download the software, or a USB drive containing the installer
The email you received with the “status’dat” license file. This was sent when the hardware was shipped. If you don’t have this – maybe you can’t find the email, or maybe it was sent to a colleague who placed the order, call or email us and we’ll re-send it right away.
Now, let’s install SoundCheck. If you’re already a SoundCheck user and you’ve just acquired new hardware, you can skip ahead to where we configure the hardware.
First insert the SoundCheck hardware key into one of your computer’s USB ports. The drivers for this key are included in the software installation, so we want it plugged in early.
00:30
Now let’s install the software. The download link is in the email with the license status.dat file. Again, if you need us to re-send this, please give us a call or email. I’ve already downloaded it, so it’s here…the setup executable.
Let’s click to install it… You may need to temporarily disable anti-virus or security settings..
If you’re on a Windows machine installing it for the first time, it may prompt you to re-boot to finish installing the LabVIEW Runtime engine – this is normal, and SoundCheck will resume automatically after the reboot.
Don’t forget to register your software and hardware – this will ensure you’re kept up to date with any new versions or software patches, and also ensure speedy support should you run into any issues that you need help with.
Now let’s open SoundCheck.
You can see it starts off in demo mode – that’s just because we haven’t activated the software yet. When you open SoundCheck, the setup wizard pops up automatically, and prompts us to locate our status.dat file… Make sure you’ve saved this somewhere you’ll remember on your computer. Note that this file is key-specific, so if you’re installing multiple systems, you’ll want to make sure you have the status file that matches the key for that system. Also, if you’re installing multiple systems, you can put all the license files in the same directory and SoundCheck will automatically select the status.dat file that matches the connected key. Make sure you select the “Current Folder” option instead of “Open” if you are doing this.
Next it prompts us to import settings from a previous version of SoundCheck. If this is your first time using SoundCheck, you can ignore this.
Now we’ll connect and configure our AmpConnect 621. If you have SoundCheck open, exit it – you want to have the 621 connected before you open SoundCheck.
Plug in the AmpConnect 621’s power cable. Then connect the 621 to your computer with the USB cable, and power it on.
Now open SoundCheck.
Because we plugged the unit in already, SoundCheck automatically recognizes the AmpConnect 621. If your device isn’t discovered, try disconnecting and reconnecting the USB cable and powering the device off and on. Now let’s configure it.
Select ‘Hardware’ from the setup menu and go to the hardware table. We’re on the “audio” tab at the top, and we can see all the input and output channels for the AmpConnect 621 have been automatically populated. Parameters such as the input and output peak voltage (Vp) values are stored on the device firmware and loaded automatically, so you don’t need to type them in. Before we save and close this, let me show you the hardware configuration. Here you can select the AmpConnect 621, hit ‘read settings’ and this is where you can see what the current settings are. After this is configured, every time SoundCheck starts up these settings will be set on the AmpConnect. For now we don’t need to change anything here as Self Test and Complete Test will configure this for us using message steps. This is good to know for when you are writing your own sequences, troubleshooting, or would like to assign a different start-up configuration. We’ll click ok, and hit ‘Save‘ to close the editor.
To finish off, we’ll run a self-test to make sure everything is communicating correctly. Go to File > Open
Navigate to the ‘Sequences\Calibration’ folder. I’m going to select ‘AmpConnect 621 Self Test 2 Channel’ because I’m just using two of the inputs on a 2 channel system; if you have an 8 channel or higher system, you can use the AmpConnect 621 self test below this one.
We get a document with more information about this sequence, I’ll just close that. And let’s hit the Green Start button – or you can use the F2 keyboard shortcut – to run the sequence.
This test configures the AmpConnect to internally loop back the outputs to the inputs, and it makes sure that it’s able to send and receive signals without relying on external cables or transducers. This can be used as a sanity check to make sure that everything in SoundCheck’s hardware table is set properly and there is no issue with the device.
And we can see, this unit has passed self-test. Now there’s just one more thing to note: here there’s a little note to alert us that if the latency is more than plus or minus one sample, the default needs adjusting. We can see our latency here is minus 2, so let’s just fix that.
We’ll go back into our hardware table and we’ll subtract 2 from our latency number and save that. Now let’s re-run the self test and we can see our latency is now within range.
Self-test is an important step – don’t skip it!
Now everything is configured we’re ready to make a measurement. Let’s do a quick demo.
I’m going to run a basic test on a loudspeaker.
You’ll need a measurement microphone to capture the response. Here I have an SCM microphone, I’ll connect this via a BNC adapter to mic input 1. And let’s connect my speaker to the amplifier output and power on…and check the speaker and microphone are correctly aligned. It’s that simple – now we’re ready to test.
SoundCheck comes with lots of pre-installed test sequences to get you up and running quickly.
Let’s open up the ‘Complete test using AmpConnect 621′ sequence from the Loudspeakers folder. You can see there’s an instructions document there if you want to learn more about the test.
Before we run the sequence, let’s double check our routing and signal paths. We can see here in the sequence editor that the acquisition step uses Mic 1, Amp 1, and Impedance 1 as our signal paths. SoundCheck automatically created these signal paths in calibration, and we can see here they are automatically set to the appropriate hardware channel. Now let’s hit run.
And there you can see, we’ve got measurements for frequency response, impedance, THD, and more from one sweep.
And that’s it. You are up and running. For more resources, visit the Listen support site or check the manuals included in your installation. And if you have any problems with your installation. We’re here to help – just give us a call or email support@listeninc.com.
How do you measure devices that can’t be directly connected to an audio interface? In this video, we demonstrate how to measure open loop devices such as smartphones and smart speakers using SoundCheck. You’ll learn how to generate a stimulus file, play it back from the device under test, and use triggered recording with a microphone and audio interface to capture the response for analysis. This flexible technique allows accurate measurement of frequency response, distortion, THD, and Rub & Buzz – even when playback and recording are asynchronous.
Video Transcript: How to Measure Open Loop Devices
Devices like smartphones and smart speakers can be challenging to test as they can’t be directly connected to conventional interfaces to make audio measurements. This means playback and recording are asynchronous.
To make accurate measurements, we use a technique called open loop testing. This lets us manually load the stimulus signal onto the device and play it using a triggered record. This means SoundCheck starts recording the response once it hears a certain sound. This might be a level threshold, or a specific frequency, or even a chirp. Once it hears that trigger it will begin the acquisition, record the stimulus, and then analyze it as normal.
Let’s take a look. I’m going to use a standard test sequence that comes with SoundCheck, but first let’s look at our test configuration.
We’re using SoundCheck to create the stimulus file, and we’ll load that manually onto our device – you can send it by email or download via the cloud, or even store it in the device firmware. We’ll then run the sequence, and play the test signal from the phone. When the trigger tone is detected, the software will start recording using an SCM microphone which is connected to the software via an AudioConnect 2 audio interface, and analyze the response.
Let’s go ahead and run the test.
The sequence is giving me the option to create the stimulus files ready to load onto the device, but I’ve already done that so I’ll just decline and let the sequence continue….
Now it’s listening for the trigger. I’ll play the sound…. And you can see, it went ahead and captured the response – we have our recorded time waveform here. Over here we have our fundamental, and also the second and third harmonics. Down here we have THD and Rub & Buzz, and over here we have perceptual Rub & Buzz. You can see we’ve got some distortion across the spectrum, and some Rub & Buzz at low frequencies – that’s not really a surprise – phone speakers tend to be small and inexpensive so these issues are common. Once you have the waveform captured you can run any analysis or calculation on it, so if you wanted, you could add other measurements to this test.
Now that we’ve seen it in action, let’s go back to the sequence and learn a bit more about triggered recording. We’ll start with the stimulus.
As you see, we still have a standard stimulus step from XHz to YkHz, but when we look at it closer we can see that it has two sections. First we have a frequency log chirp that tells SoundCheck when to start recording. This is much more robust than simple level or tone triggers, especially if you’re in a production environment where you might have background noise or even pick up test tones from other lines. And you can see here we’ve set it so that this portion of the stimulus does not get analyzed.
The second portion of the stimulus is our test signal – a standard frequency stepped sweep from 10kHz down to 100Hz and we have ‘analyze’ set to ‘yes’ for that one.
The acquisition step must also be configured for triggered record. Here, we make sure the ‘triggered record’ checkbox is checked, and then select the type of trigger that we’re using. We used ‘level and cross-correlation’, which looks for the specific chirp that we used – that one is the most robust but we also offer simpler level and frequency triggers.
So, as you can see, open loop measurements are simple with SoundCheck. This method can be applied to any device that doesn’t have a direct connection like smart speakers, smart glasses, phones or even robots. Check out our website to learn more.
https://www.listeninc.com/wp/media/2026/03/Open-Loop-Demo-TN-scaled.png14402560Julius Wijonohttps://www.listeninc.com/wp/media/logo.pngJulius Wijono2026-03-11 15:53:332026-08-28 14:29:19Open Loop Test Measurement
Normalized Distortion, or Frequency Normalized Distortion, is a distortion measurement algorithm first proposed by Listen’s president, Steve Temme (then at Bruel and Kjaer) in a 1993 AES paper. Although it’s been available in SoundCheck since 1996, it’s only recently gained traction. This is likely due to a renewed interest in correlating measurements to audibility – something that we’ve always considered important at Listen – and also because it is the only way of accurately measuring some new types of microspeakers. Let’s take a look at how it differs from conventional distortion measurement and why it is valuable for identifying the cause of distortion.
A typical speaker response, shown in Fig. 1, isn’t flat. There are typically amplitude irregularities due to reflections and resonances, and high and low-frequency roll-offs due to the passband nature of the transducer. This introduces some interesting artifacts when we look at harmonic distortion.
Fig. 1. Typical loudspeaker response
Fig. 2 shows the fundamental, second and third harmonic of a speaker. If we’re measuring harmonic distortion by sweeping from 20 hertz to 20 kHz, to measure the second harmonic, our filter tracks at twice the stimulus frequency and goes out to 40 kHz. Let’s assume that the second harmonic is 20 dB below the fundamental, i.e. 10% distortion. The third harmonic starts at three times the fundamental frequency and goes to 60 kHz, and let’s assume that this harmonic is 40 dB down below the fundamental, or 1% distortion. You can see the bumps and dips in the response align with the fundamental as the harmonics are filtered by the same linear frequency response.
Fig. 2. Loudspeaker response with second and third harmonics at their measured frequencies
The problem with conventional THD is that we always plot the harmonics at the stimulus frequency and then we compare the harmonic level to the stimulus level at the stimulus frequency as shown in Fig. 3.
Fig. 3. Loudspeaker response with second and third harmonics shifted to stimulus frequency
You can see that the responses are shifted along the x-axis to start at 20 Hz, like the stimulus frequency. This change in alignment between the harmonics and the stimulus causes the irregularities to be offset, and the high and low-pass roll-offs look entirely different.
Fig. 4. The effects of aligning harmonics with the stimulus before calculating THD
When we now calculate THD, (Fig. 4) we get some interesting results. Even though we showed earlier that the second harmonic was uniformly 20 dB down, when we calculate it this way, the distortion appears much higher at low frequencies because the fundamental rolls off sooner. Instead of being -20 dB (or 10%) at 20 Hz, it’s actually only -3 dB, which is equal to 71% distortion.
We see the opposite effect at high frequencies; the distortion rolls off prematurely compared to the stimulus frequency. This means it’s calculated to be -30 dB, or 3.1%, rather than -20 dB (10%).
In the pass-band region, the distortion could be under, or over-estimated, particularly around the resonances and reflections, where the calculation differences are more pronounced. This isn’t limited to the second harmonic; it’s the same for the 3rd and any subsequent harmonics so all these differences stack up.
If you look at a typical THD measurement of a loudspeaker, you’ll notice it’s always high at the lowest frequencies and rolls off at high frequencies. This is because conventional distortion measurement methods tend to over-estimate distortion at low frequencies, and under-estimate it at high frequencies.
So why does this matter? If you want to truly understand what’s causing your distortion, you need to separate the linear from the nonlinear. The good news is that this isn’t difficult – it’s just a small change in the order of operation when the THD is calculated.
What we proposed back in 1993, and I am still a strong advocate for today, is calculating it as follows: Instead of plotting the harmonics at the stimulus frequency and comparing it to the fundamental at the stimulus frequency, reverse the order. Plot the harmonics at the actual measured frequencies, compare it to the fundamental at the harmonic measured frequency, calculate the percent distortion, and then plot it at the stimulus frequency (Fig. 5). This is what we call Frequency Normalized Distortion.
Fig. 5. THD measurement when THD is calculated before aligning harmonics with the stimulus
If you’re wondering why this looks familiar, it’s because the graphs and distortion calculations exactly match the actual distortions shown in Fig 2.
As well as removing the influence of the linear frequency response on the calculated distortion, this method also minimizes the influence of room reflections. This enables you to measure the free field harmonic distortion in a regular untreated room with reflections – a particularly useful technique if you’re measuring somewhere like a car, which is full of reflections.
Now we’ve covered the theory, let’s examine some real-world examples: a conventional speaker and a piezo-MEMS speaker.
Fig. 6 shows the measured harmonics for a dynamic speaker driver. The fundamental starts at 50 Hz and the 2nd and 3rd harmonics are plotted at their measured frequencies, starting at 100 Hz and 150 Hz respectively. The roll-offs are clearly similar at the low frequencies, as expected. At frequencies above around 8 kHz, the shape of the third harmonic is particularly similar to the fundamental, clearly demonstrating its linear filtering effect. Even the second harmonic shows some similar characteristics.
Fig. 6. Measured harmonics for a dynamic speaker driver.
Fig. 7. Conventional and Frequency Normalized THD
Fig. 7 shows the THD plotted both the conventional way (purple line) and the normalized way (green line). The conventional plot indicates around 10% distortion in the lower frequencies, and a bump around 200 Hz – which could potentially be a problem. The reality, however, is that it’s just the linear response boosting the low frequencies. The conventional plot also has a little bump around 1 kHz, but this is caused by the slight bump in the fundamental curve at higher frequencies. If we now look at the frequency normalized curve, it’s clear that we don’t have a low-frequency issue, although we do have a little bump at resonance around 300 Hz – and that is indeed a nonlinearity. This is much more valuable information if you need to know precisely where the distortion is coming from so that you can design around it.
The differences between conventional and frequency normalized distortion are even more significant with piezo-MEMS transducers. Piezo-MEMS transducers are an interesting new class of miniature transducers that use semiconductor fabrication processes to create actuators with piezoelectric materials that drive a membrane, rather than traditional mechanical components. They behave very linearly in the lower frequencies – you typically don’t see any increase in distortion at all – but often have a little high-frequency resonance. Due to these characteristics, a major vendor of these devices advises their customers that Frequency Normalized Distortion measurements are a critical part of accurately assessing distortion.
Fig 8. shows the measured fundamental and harmonics of a piezo-MEMS speaker plotted at their measured frequency, and Fig. 9 shows the same harmonics plotted at the stimulus frequency.
Fig. 8. Harmonics plotted at measured frequency for a Piezo-MEMS speaker
Fig 9. Harmonics plotted at stimulus frequency for a Piezo-MEMS speaker
In Fig. 8, the shape of the third harmonic again clearly mirrors the fundamental, and the second harmonic has something going on – maybe a resonance – close to 10 kHz. In Fig. 9 where the harmonics are plotted at the stimulus frequency, the low-frequency distortion, as before, appears a lot more significant than in Fig. 8 where it is plotted at the measured frequency.
Fig. 10. Conventional and Frequency Normalized THD for a piezo-MEMS speaker
This is clear in Fig. 10, where we compare the conventional and Frequency Normalized THD. Plotted the conventional way, the distortion is calculated at around 20% at 100 Hz, which is quite high. However, when calculated the frequency normalized way, it’s down at 6-7% . It’s also quite flat throughout the 100 to 10 kHz range, which is typical of these drivers. They’re simpler – there are fewer components to cause distortion, and they’re not acting in a nonlinear magnetic field. As with the traditional driver, relying only on conventional THD measurements could lead to a lot of wasted time trying to design around problems that don’t exist.
Whenever I explain this distortion measurement method, most engineers immediately recognize its benefits, and wonder how the conventional method became the norm. I suspect the reason traces back to early measurement practices: in the 1980s, Bruel & Kjaer pioneered the tracking-filter method, and plotting harmonics at their actual measured frequencies simply wasn’t possible with the chart recorders that were in widespread use. That constraint shaped the convention we still use today, even though the technological limitations that created it no longer exist. Perhaps the demands of modern transducer technologies may finally drive the industry to adopt it.
Summary
Conventional and Frequency Normalized distortion measurement methods are compared in Fig. 11. Conventional THD isn’t wrong. If you listen to sine waves it is what you hear. However, we don’t generally listen to sine waves, and Frequency Normalized Distortion correlates better with listener perception of broadband signals such as speech and music.
More significantly, to correctly identify distortion mechanisms, and design products that address these, it’s essential to separate the linear response from the nonlinear distortion, and this requires Frequency Normalized Distortion.
Fig. 11. Comparison of conventional and Frequency Normalized distortion
Check out the recording below to learn more on Frequency Normalized Distortion: Why THD Isn’t Enough:
https://www.listeninc.com/wp/media/2025/12/Fig-2_LR.png437630Julius Wijonohttps://www.listeninc.com/wp/media/logo.pngJulius Wijono2025-12-12 15:16:362026-08-12 12:51:59The Value of Normalized Distortion
https://www.listeninc.com/wp/media/2025/12/Fig-2_LR.png437630Julius Wijonohttps://www.listeninc.com/wp/media/logo.pngJulius Wijono2025-12-10 14:13:522025-12-12 15:00:44The Value of Normalized Distortion
Easily calibrate your measurement chain by importing correction curves directly into SoundCheck. In this video, we’ll show you how to load external data, apply it to a signal path, invert response curves when needed, and ensure your corrections are properly applied during analysis for accurate test results.
Additional Resources for SoundCheck
Detailed explanations of how to use SoundCheck can be found in the SoundCheck manual.
Video Transcript: Importing Correction Curves for Calibration
It’s simple to calibrate signal paths in SoundCheck using either imported data or measurements you’ve made. This is useful, for example, if you need a frequency and phase correction curve for an input transducer, or a DRP to ERP correction.
To apply a calibration curve, the calibration data first needs to be in the memory list. If your data is in an external file, for example if you have a microphone frequency response curve from a calibration lab, you just select “open data” from the data menu of the memory list… and you can see now it shows up in the list. SoundCheck supports a wide range of formats from our own .dat format to txt and csv files.
Alternatively, you can use a recall step to bring your measured data into the memory list.
Now we have our correction curve loaded into the Memory List, we can use this curve to overwrite the calibrated device. Let’s open up the calibration window, and we’ll select the ‘copy from memory list’ button and choose our source curve. You can either apply the curve as it is, or invert it using this “invert curve” checkbox. You would use this, for example, if you want to remove the frequency response curve of the microphone from your measurement.
So, let’s check that box, and we’ll hit “apply” to save it, and OK.
Now we’ve added the appropriate correction curve to the signal path, the final step is to apply this new correction to our input response by enabling the checkbox “Apply Correction In” in the analysis step. It’s important to make sure this is selected otherwise, the correction will not be applied.
https://www.listeninc.com/wp/media/2025/11/Correction-Curves-Blog-TN.png10801080Julius Wijonohttps://www.listeninc.com/wp/media/logo.pngJulius Wijono2025-11-25 05:00:562026-08-27 14:03:06Importing Correction Curves for Calibration
Quickly explore new analysis options without modifying your original sequence. Learn how SoundCheck’s Offline Processing tools let you run individual steps manually, generate protected data, and easily compare results.
Additional Resources for SoundCheck
Detailed explanations of how to use SoundCheck can be found in the SoundCheck manual.
Video Transcript: Quickly Analyze Data with Offline Processing
In SoundCheck, there might be times where you want to further process data that’s already captured. This could be from a sequence run or even data that was acquired on a completely different computer.
For example, in this sequence here,I ran an acquisition and got a frequency response with a time selective response. I might want to change some settings, and I might want to manipulate this data further. I could go into my analysis step and make changes, or drag in additional post-processing. But if I’m just trying to investigate, I might not want to change the sequence that I’ve been using.
Here we can use the Offline menu. This lets us run any step in SoundCheck, but instead of in a sequence, we just run it manually.
So when I open up Offline Analysis, I can choose any step templates that are available in my Sequence Editor. Lets choose Time Selective Response analysis, and it opens up the editor.
Now I can manually manipulate this, choose whatever settings I want, and then when I apply these settings, it will create protected data in my memory list with these settings. So here, I’ll configure my step, and pick my stimulus and response waveform. Now let’s say I want to see how this would look with a different windowing time. I just type in the new value here, click Apply, and this data is populated to my memory list as protected data.
I can view this alongside the measured data in my sequence to see what the changes would be. And I can keep doing this— every time I make a change and click Apply, I’m going to get additional protected data. It’ll be added to the memory list, and I can go through, quickly view these, and see which setting I want.
This is also useful for additional processing. If I close this step, I can delete the data I captured over here from the memory list, and I can process this curve further. Instead of changing a step that I already ran in the sequence, I can add in a completely new step.
For example, If I want to see the maximum value on this curve, I can open up a Post-Processing step… look look at the Maximum template…. choose my Fundamental, and when I click Apply, it’s added to my memory list, and I can view it on this table here.
The Offline menu gives a very quick and easy way to add new measurements and further process your data from a single menu without needing to write an entire sequence.
https://www.listeninc.com/wp/media/2025/05/SoundCheck-Offline-Blog-TN.png10801080Julius Wijonohttps://www.listeninc.com/wp/media/logo.pngJulius Wijono2025-05-13 08:00:172025-05-12 10:56:37Quickly Analyze Data with Offline Processing
Standardized measurement of in-car audio systems remains an ongoing challenge, particularly regarding microphone configuration and placement, test signals, and correlation with perception. Current recommendations from the AES Technical Committee on Automotive Audio (TC-AA) advocate spatial averaging using multi-microphone arrays to improve repeatability.
