100 Things #97: Zwicker Loudness Measurement

Zwicker Loudness Measurement, an indication of overall perceived loudness level, is calculated in SoundCheck using the Zwicker Loudness post processing step. Instead of just measuring the absolute sound pressure level in dB SPL relative to 20uPa, the Zwicker Loudness algorithm takes into account how humans hear sound level using  the PEAQ international standard. This is an ITU-developed standardized algorithm for objectively measuring perceived audio quality as subjects would in a listening test.

Zwicker Loudness Measurement

Learn More About SoundCheck’s Advanced Features

Read more about more measurement features in SoundCheck.

More information is also available in the  SoundCheck Manual.


Video Script: Zwicker Loudness Measurement

Did you know that SoundCheck can calculate the overall perceived loudness level using a Zwicker Loudness post processing step ? Instead of just measuring the absolute sound pressure level in dB SPL relative to 20uPa, the Zwicker Loudness algorithm takes into account how humans hear sound level using  the PEAQ international standard. This is an ITU-developed standardized algorithm for objectively measuring perceived audio quality as subjects would in a listening test.

The input to this post processing step must be a spectrum of a complex signal in pascals or dBSPL. We can easily capture this in SoundCheck using an FFT or RTA broadband measurement using a calibrated Reference Mic signal path. To simulate the non-linearity of the ear, the Zwicker Loudness algorithm then filters these frequencies into auditory bands according to the bark scale – a frequency scale where equal distances correspond with perception. Once the spectrum is plotted on a bark scale, a frequency weighting is applied that correlates to human hearing. Finally, a level compression is applied and the loudness is output in Phons and Sones. The loudness spectrum can optionally be shown with the X axis either in Hertz or Bark.

Knowing the actual perceived loudness of a signal is extremely important for certain applications. For example, listeners that are trying to subjectively compare different headphones will be biased towards the louder one. If I want users to subjectively compare two different headphones, I need to make sure they are played back at the same level to avoid this bias. Looking at the 1kHz sensitivity of each headphone doesn’t take into account the difference in frequency response across the two devices. Often A-weighting is used to correlate measurements to human hearing, but a simple A-weighting curve makes a lot of assumptions such as what level of playback that will be used. Zwicker Loudness gives us a much more accurate perceived loudness, and enables us to precisely match the loudness, in phons, between the two devices regardless of level..

Zwicker Loudness is also widely used in communication testing for measuring loudness of both speech transmission, and ringtones. Check out our website to learn more.


100 Things #95: Time Domain Waveform Filtering

Time Domain Waveform Filtering in SoundCheck lets you apply any filter to a signal in the time domain instead of the frequency domain. This enables you to apply a filter, such as an A-weighting filter, without affecting the peaks or crest factor of the signal. Filters can also be applied to any waveform in the memory list, such as the stimulus, response, or any intermediate waveform. Watch this short video to learn how standard and custom waveform filters are used.

Time Domain Waveform Filtering

Learn More About SoundCheck’s Advanced Features

Read on about more measurement features in SoundCheck.

More information is also available in the  SoundCheck Manual.


Video Script: Using Time Domain Waveform Filtering in SoundCheck

Waveform filtering in SoundCheck lets you apply any filter to a signal in the time domain instead of the frequency domain. This is required when you want to apply a filter, such as an A-weighting filter, without affecting the peaks or crest factor of the signal, e.g. peak sound pressure level, A-weighted. It can also be applied to any waveform in the memory list, such as the stimulus, response, or any intermediate waveform.

Both standard and arbitrary filters are available. Standard filters include lowpass, highpass, bandpass and bandstop filters. You can select the cutoff frequencies, and control the slope of the filter using the filter order. SoundCheck’s standard filters are implemented as IIR Butterworth filters, and are ideal for most applications where you need to attenuate certain frequency ranges. For example, you can use a high-pass filter to remove some low frequency background noise or remove dc offset. Alternatively, you might use a lowpass filter to attenuate alias frequencies that could cause your amplifier to clip at very high frequencies that are not of interest.

You can also create your own arbitrary waveform filter by applying any curve from the memory list to the waveform. This can be used to apply weightings such as K-weighting for loudness or a bandpass filter  to a speech stimulus. Or you can even specify your own custom weighting or equalization, for example to see what happens to a customer’s speaker when they boost the bass.


100 Things #93: Group and Batch Processing of Data Curves

Group and Batch Processing is a really neat feature in SoundCheck that saves huge amounts of time when processing data. Curves, values and waveforms can be grouped and processed together, and the analysis, post processing or statistics runs almost as quickly as on a single piece of data. This can be done during a sequence, or offline with previously collected data. It even extends to imported data – for example, if you want to run a POLQA analysis on a batch of recordings made in a different system, you can simply import the wav files and calculate scores for hundreds or even thousands of waveforms all at once.

Save Time Processing Data with Group and Batch Processing

Learn more

Read our Knowledgebase Article on using batch processing.

Learn more about the POLQA module in SoundCheck (video contains a demo of batch processing).


Video Script:

Audio test and measurement involves collecting and analyzing a lot of data. You might have multiple inputs and outputs, or you need to collect data not just once but over and over again. Perhaps you’re averaging measurements on a single unit over multiple runs, or testing multiple units in a production facility. Handling and processing all this data efficiently, in realtime, can be complex.

SoundCheck processes large groups of data quickly and easily with its group and batch processing capabilities. Curves, values and waveforms are grouped and processed together, and the analysis, post processing or statistics runs almost as quickly as on a single piece of data.

This is useful, for example, if you’re repeating a series of sequence steps on a single device, to calculate the deviation in its response at various positions, or if you’re averaging sensitivity values of a batch of 15 microphones for a spec sheet.

Groups of data can be analyzed and processed either within a test sequence or offline.

In a sequence, groups of data can be automatically created, saved in the Memory List and automatically analyzed together the same way every time the sequence is run. Here’s a simple example sequence where I capture recordings using a 6 mic array, group the recorded waveforms and use a single analysis step to get responses from each of the microphones. The same process can also be used in post processing or limit steps. SoundCheck also makes it easy to keep track of your data by allowing you to append your data names with Signal Path and Input data names.

Data processing outside of a sequence is known as “offline mode” – let’s take a look at an example. Here, I’ll group the frequency responses of 5 microphones I measured previously and calculate their sensitivity values at 1kHz in a single post processing step, rather than using 5 such steps. Note how fast it is in both cases!

SoundCheck’s batch processing capabilities even extend to imported data. For example, if you want to run a POLQA analysis on a batch of recordings made in a different system, you can simply import the wav files and calculate scores for hundreds or even thousands of waveforms all at once.

SoundCheck’s batch processing capabilities handle large amounts of data extremely fast, helping both R&D labs and production facilities to reduce test times. To learn more about SoundCheck’s extensive audio measurement toolkit, check out www.listeninc.com.


100 Things #92: Continuous Log Sweep with Time Selective Response Analysis

Did you know that SoundCheck was the first audio test system to implement the continuous log sweep stimulus, way back in 2001. Also known as a frequency log sweep, or Farina sweep, this stimulus is used with time selective response (TSR) analysis. TSR analysis allows reflections to be windowed out, making it great for loudspeaker simulated free field measurements and room acoustics measurements. It’s also valuable as a smart trigger for robust open loop measurement testing. Watch this video for a quick overview.

Continuous Log Sweep with Time Selective Response Analysis

Learn more

Read on about stimulus and analysis capabilities in SoundCheck.


Learn more about Simulated Free Field Measurements

Short Video Demonstration of free field measurements without an anechoic chamber

Full-length Demonstration of free field measurements without an anechoic chamber

Article explaining simulated free field measurements (reprinted from Voice Coil Magazine)

The Original 1992 paper introducing the Simulated Free Field Measurement Technique


Learn more about room acoustics measurements using the Log Sweep Stimulus

Full-length Demonstration of Room Acoustics measurements


Video Script:

Did you know that SoundCheck was the first audio test system to implement a continuous log sweep stimulus? We introduced it back in 2001,  shortly after Angelo Farina’s landmark AES paper on the subject. Let’s take a look at how it works and how it’s used.

A continuous log sweep, sometimes known as a frequency Log sweep or Farina sweep,  is a continuous sine sweep with equal time and energy in every octave. Since it sweeps slower at low frequencies but speeds up as the frequency increases,  it’s a great choice for fast measurements. It differs from a conventional stepped sine stimulus, in that the continuous log sweep plays across all frequencies in the range with a defined sweep rate per decade, whereas the stepped sine sweep “steps” through different frequencies across the range.

Both stimuli can measure frequency response and harmonic distortion, but the analysis methods differ. A continuous log sweep uses a time selective response, or TSR analysis. This involves calculating an impulse response and applying a user-defined time window that can isolate or  remove any reflections caused by the test environment. A stepped sine requires a HarmonicTrak analysis. Only the continuous log sweep with TSR analysis can window out reflections, allowing a simulated free field measurement even when you are not in a fully anechoic environment.

Let’s take a look. In the TSR analysis step, we’ll enable this checkbox here to output an impulse response to the memory list so we can view it. It can be displayed either on a linear or logarithmic scale.  The window size at the top is where we define the start and stop points of the window that’s applied to the impulse response. We can look at this in SoundCheck to help us decide which points to use. Here, we can clearly see a large impulse that has been autodelayed to 0 seconds to show the direct sound from our sound source. And because we’re in a non anechoic environment, just a normal room, you can see reflections from the walls, floor, ceiling, table etcetera.  in the impulse response. We can adjust the window to remove them, and you can see the frequency response updates. 

This technique is very powerful, but like all techniques there are tradeoffs. So Log TSR analysis might not be the best option for all applications. The measurement resolution is affected by the window size – as the window size narrows,  the frequency resolution reduces, and you can see the effects on the frequency response. This is particularly noticeable at the lower frequencies where  the lack of resolution can make the data inaccurate if the window is too small. We need to be careful to configure the window size to capture the direct sound but be wide enough to get the greatest frequency resolution, without any reflections due to the test environment.

TSR Analysis  offers significant benefits for several applications. We use it for the high frequency measurements in a loudspeaker simulated free field measurement, which we can then splice together with the low frequency Stepped Sine Sweep stimulus measurement. It’s also valuable for room acoustics, for example, for calculating RT60 and clarity measurements. And if you’re running open loop tests, our cross-correlation smart trigger uses a continuous log sweep to provide a way of triggering an open loop measurement that is extremely robust and far less susceptible to false triggers than other methods. 

To learn more about the applications of a continuous log sweep stimulus, check out the technical papers and demo videos on our website.

100 Things #91: Measurement of Intermodulation Distortion

Intermodulation Distortion measurements are a great alternative to harmonic distortion for measuring narrowband devices such as hearing aids and communication devices. In such devices, harmonic distortion measurements tend to underestimate the distortion as the higher-order harmonics fall outside the pass band of the device. In this short video, Steve Temme demonstrates and explains the two IM distortion measurement options in SoundCheck – intermodulation distortion and frequency distortion and discusses how they can be used for low frequency speaker measurements, narrowband devices and microphones.

Measurement of Intermodulation Distortion

Learn more

Read on about more analysis capabilities in SoundCheck.

Video Script:

Although harmonic distortion is perhaps the most commonly measured distortion metric, it’s often not ideal for measuring narrowband devices such as hearing aids and communication devices. These products often have a high frequency cut-off around 3-5 KHz, so the higher-order harmonics fall outside the pass band of the device, so harmonic distortion measurements often underestimate the distortion.

A useful alternative we offer in SoundCheck is intermodulation distortion. Intermodulation distortion relies on the interactions between two simultaneous pure tones to produce measurable intermodulation products. These measurements actually present a more realistic representation of real-world signals such as speech and music that are rich with intermodulation products than the single tone used in harmonic distortion

SoundCheck offers two intermodulation distortion measurement options – Intermodulation Distortion and Difference Frequency Distortion. For Intermodulation Distortion, we superimpose a sweeping frequency tone against a fixed frequency tone. For Difference Frequency measurements, we use a stimulus consisting of two sweeping tones separated by a specified frequency interval, which can be a fixed difference or a fixed ratio. These are fully customizable.

In both cases, the two signals interact to produce intermodulation products. With Intermodulation Distortion, these are equal to the sum and difference of the upper frequency and integer multiples of the lower frequency. Difference Frequency distortion, only considers the components that are the difference and multiples of the difference, between the excitation frequencies.

Each type has its own specific applications. For example, Intermodulation distortion is mostly used for loudspeaker measurements, particularly at low frequencies, and Difference Frequency distortion is ideal for testing narrowband devices as the frequencies can be chosen so that the intermodulation products mostly fall within the pass band. This is easy to do in SoundCheck – simply configure your two test stimuli, and select your analysis – either Intermodulation Distortion, or Difference Frequency Distortion – in the analysis editor.

Intermodulation distortion is also a valuable technique for measuring microphones. Usually, the harmonic distortion from the source speaker playing the test tone is greater than the harmonic distortion that you are trying to measure from the microphone. However, if separate test tones are fed individually to two separate loudspeakers, the loudspeaker’s harmonic distortion has no influence on the measured intermodulation frequency components, enabling accurate measurement of the microphone’s intermodulation distortion.

To learn more about intermodulation and other types of distortion, check out our website, and stay tuned for a new in-depth seminar on distortion.

100 Things #90: Curve Smoothing

Curve smoothing in SoundCheck allows for non-destructive processing of data, resulting in smooth and easy to visually understand curves. Curve smoothing can lessen the effects of reflections in the test space, reduce noise, or make curves less jagged for publishing data. The smoothing post processing step in SoundCheck features an array of different, to facilitate different levels of the smoothing process, including various smoothing widths and windowing options.

Curve Smoothing

Learn more about SoundCheck post processing options

SoundCheck has a full suite of post processing capabilities including curve smoothing, resampling, resolution, curve arithmetic, and more.  Read more details in our SoundCheck features and applications section.

Each sequence uses a stimulus configured to the device under test, and recommended hardware.

Video Script:

Curve smoothing, as its name suggests, is a useful post-processing option that turns your jagged lines into smooth curves. It  may be applied to a curve for a number of reasons – to reduce the appearance of noise in the signal, to minimize reflections and other artifacts from the measurement environment, or simply to make a curve look better for presentation in sales and marketing literature. When smoothing is applied, the points of the curve are modified so that individual points that are higher than the immediately adjacent points are reduced, and points that are lower than the adjacent points are increased.

SoundCheck uses sliding-average smoothing also known as “boxcar” averaging where each point in the curve is replaced by the average of n adjacent points where n is a positive integer known as the smoothing width.  SoundCheck supports standard 1/n octave smoothing widths from one octave to 1/24th octave as well as user defined log and linear values.  In addition to a default rectangular window, a Hanning window may also be applied during the smoothing function. Smoothing is symmetrical at the midpoints of the curve but tapers to zero at the curve’s end-points.  If the curve has uneven or non-standard spacing in the frequency domain, interpolation is used.

In addition to the standard Smoothing post-processing step, the smoothing function is also available in the Resolution post-processing step. This is useful when the final curve resolution is higher than or “not a mathematical factor” of the original resolution.

This feature’s been available in Soundcheck since it was launched in 1995. If you haven’t tried it yet, check it out!

100 Things #87: Make Non-Coherent Distortion Measurements

Did you know that you’ve been able to make distortion measurements in SoundCheck with real-world signals such as speech and music since 2006? This is a valuable technique for testing modern devices with on-board DSP that filters out signals such as sine waves and noise. Non-coherent distortion measurements offer excellent correlation with perception and are easily implemented in SoundCheck. Steve Temme explains this technique in this short video.

Make Non-Coherent Distortion Measurements

Read more about making non-coherent distortion measurements

The 2006 AES paper on non-coherent distortion measurements is available to read from our technical papers library. This paper details all of the important considerations for making these measurements, including using a multitone versus music for a stimulus signal, understanding distortion measurement results, and more.

Video Script:

We talk a lot about harmonic distortion and transient distortion, but did you know SoundCheck also offers non-coherent distortion measurements? In fact, I believe we were the first audio measurement company to include this option.

Non-coherent distortion is a broadband distortion metric that includes harmonic and intermodulation distortion as well as noise. It offers better correlation to perception than harmonic or intermodulation distortion alone, and it can be used with real-world test signals such as speech and music as long as there is enough energy in the frequency range of interest. Otherwise, you might just be measuring background noise. I usually make these measurements in the nearfield to reduce background noise by placing the microphone close to the loudspeaker. This is particularly useful for the many modern devices that feature DSP that treats pure tones as noise and tries to filter them out.

Non-Coherent Distortion is a normalized cross-correlation measurement that determines the degree to which the system output is linearly related to the system input.

There’s a lot of complex math behind this – if you want to know more about that you can read our 2006 AES paper. Here, I’m just going to show you a quick demonstration.

Configuring non-coherent distortion in SoundCheck is a simple checkbox in the transfer function analysis editor.

I have a good speaker, and a speaker that exhibits some fairly significant distortion. Let’s look at the good speaker first. I’m going to play a short excerpt of Bird On A Wire at 90dB SPL by Jennifer Warnes – this song is widely used as a test track as it has good dynamic range.

And if you look at the results, you can see non-coherent distortion in percent per square root Hertz (spectral density) versus frequency. Since non-coherent distortion uses a broadband test signal for measurement, there is no direct correlation to harmonic or intermodulation distortion in percent. Typically the distortion level appears much lower than harmonic or intermodulation distortion because the test signal energy is spread out over the entire frequency range and not a single frequency for measuring harmonic distortion.

Now I’m going to play the same song on a speaker that I know shows some fairly heavy distortion

Now, looking at these results, you can see the non-coherent distortion is considerably higher than the good unit, especially at low frequencies.

So that’s it. Non-coherent distortion offers a way of measuring transducers with real-world test signals that correlates well to listener perception. To learn more, check out our AES papers on the subject, or download our free test sequence for non-coherent distortion measurement.

100 Things #64: Using Statistics to Create Test Limits

The statistics feature in SoundCheck adds the ability to perform a variety of statistical measurements. SoundCheck’s statistics step can work with data, results, or both. Statistics allows users to take a set of data, like frequency responses of multiple devices, and automatically calculate the best or worst fit to average, maximum, minimum, and more. This statistics functionality is not just confined to a sequence, since all the same functionality is available with offline statistics. This is a great solution of performing statistics independent of a sequence, for applications like finding golden units in production testing.

Using Statistics to Create Test Limits

Learn more about statistics and limits in SoundCheck

If you want to learn more about using statistics in SoundCheck, our four-part tutorial series on using statistics with SoundCheck is available to watch here. This series goes in-depth with statistics data, results, processing capability, and offline capability.

Our three-part tutorial series on limits in SoundCheck is available to watch here. This three part series covers the basics of limits functionality in SoundCheck, data, and advanced limit creation.

Video Script:

One question I often hear from customers is “I wrote a sequence to measure my devices. I have the frequency response, THD, sensitivity, but how do I know if this is good or bad?” We have statistics tools inside SoundCheck that can make this determination a lot easier. 

It’s important to remember that measurement targets are completely different depending on the device. For example, the acceptable level of distortion in a high end pair of bluetooth headphones, would be completely different than a cheap USB headset made for online meetings. A great place to start is picking out five units that are subjectively “good” devices. We can measure these units in SoundCheck, use statistics to help us generate limits, then compare other devices to this.

Let’s look at a standard headphone test sequence. Right now it’s configured to just run one test, but by adding in a statistics step to the end of the sequence, I can run this test as many times as I like and average all of those different units. 

The statistics step has many different features, but let’s look at Mean and Standard deviation. Mean takes the average point of the selected curve or value for every run. If I measure 5 devices and get their frequency responses, the mean is a running average of all 5 devices combined. We can use our mean as a reference curve, and compare each device to this. 

Standard deviation outputs plus minus sigma curves, which we define in the editor. For example if I want to make sure that all my devices fall within 3 sigma of my 5 reference devices, I set up my statistics step to output +/- 3 sigma, and after I run my 5 different units these upper and lower sigma curves are added to memory. I can then use these as the upper and lower limits in my test sequence, and pass a device if it falls within this range and fail it if it’s outside the range. 

And one final note… If you already captured measurements but didn’t run statistics on it while the sequence was running, all of these same features are available in the offline statistics editor. Just open up your curves from your good units in the memory list and you can run statistics directly through the offline menu.

With offline statistics, you can calculate the Best Fit to Average and Worst Fit to Average curves by finding which unit comes closest to, or furthest away from the average curve. Best Fit to Average can be used to find a reference or “Golden Unit”. This can be used as a sanity check when things go wrong on the production line and for developing limit curves. Some manufacturers prefer this approach because the factory environment e.g. temperature and humidity can vary from day to day and affect devices’ measurement performance.

By measuring the golden unit before measuring newly manufactured devices, the limits can be updated relative to the golden unit under current conditions. Worst Fit to Average can be used to find outliers or bad units that you don’t want to use in your statistical calculations when developing limits. Once you find a Worst Fit to Average curve, simply unselect it and re-run your statistics on the remaining good units. 

Do you use statistics to set pass/fail criteria? Let us know in the comments below.

100 Things #62: Make Directional Measurements with Polar Plots in SoundCheck

SoundCheck’s Polar Plots make directional measurements simple. No matter what device you are testing, whether it be a VR headset, spatial audio, or headset sound leakage, SoundCheck can automate the measurement and turntable control. This means long high resolution measurements become as simple as starting a sequence! We even have a free, prewritten directional measurement test sequence using the new Portland Tool & Die MDT-4000 turntable, available here.

Make Directional Measurements with Polar Plots in SoundCheck

Try our loudspeaker polar plot measurement sequence for yourself!

Our polar plot sequence measuring a loudspeaker is pre-written and ready to use. This sequence measures the polar response of a loudspeaker in both the vertical and horizontal dimensions and displays the measurements on polar plots. This sequence is designed to work with the Portland Tool & Die MDT-4000 turntable.

Video Script:

Making directional measurements in SoundCheck is simple! SoundCheck supports turntables from a variety of manufacturers including Outline, Linear X, B&K and of course, Portland Tool and Die. These can all be controlled through a custom step in SoundCheck to be operated as part of an automated test sequence. Let’s take a look. 

Here I have a Portland Tool and Die MDT-4000 turntable – this a great turntable, by the way.  I’m going to use this to rotate a speaker, and I have a stationary measurement microphone to capture the recorded waveform. And of course I have SoundCheck on my laptop, along with an AmpConnect 621 Audio interface.

Here’s a  simple loudspeaker test sequence that plays a test signal through a loudspeaker and measures the response. Now let’s say I want to measure the response of the speaker every 10 degrees for a full 360 degree rotation. I just need to open up the test sequence….And I am going to add a custom step telling it to rotate the speaker by 10 degrees and re-measure, saving the results in the memory list and plotting them on a polar chart, now I’m going to loop that whole measurement procedure so we continue moving it and measuring until we do a full rotation. And now I’ll edit the display step to get the results output to a polar plot. Now let’s run the sequence…and there you are – fully automated directional measurements! 

There are many ways to use this functionality, for example directional measurements on smart devices with microphone and speaker arrays. You can also put headphones or VR headsets on a rotating head and torso simulator and measure the sound leakage that occurs when the noise inside the headphones leaks outside to the point where it’s audible to others around.  There are also many applications in spatial audio measurements. 

If you want a quick way of getting started with directional measurements, head on over to our website where you can download basic directional measurement sequences for speakers and microphones for a variety of different turntables.

100 Things #55: Make RT60 Room Acoustics Measurements With SoundCheck

SoundCheck makes fast, reliable RT60 room acoustics measurements with fully calibrated signal paths, ensuring accurate results. This helps product designers quantify how their devices will interact with the acoustics of a particular type of room, and simulate real-world conditions to test their devices.

Making RT60 Room Acoustics Measurements with SoundCheck

Learn more about making RT60 Room Acoustic Measurements

The Room Acoustics Measurement video demonstrates Room Acoustics Measurements in the First Korean Church in Cambridge, MA.


Video Script: RT60 Room Acoustics Measurements

Did you know that SoundCheck can make RT60 Room acoustics measurements? This helps product designers quantify how their devices will interact with the acoustics of a particular type of room, and simulate real-world conditions to test their devices.

This is particularly important for products such as smart devices and communications devices where the user may place them in a variety of locations. Test environments to simulate these must be carefully designed and fully characterized, with known reverberation time – that’s the signal decay time,  and clarity – the ratio of early reverberation to later reverberations.

The difference between SoundCheck and the more basic room acoustics packages out there is that SoundCheck makes all the measurements with advanced filtering algorithms and fully calibrated signal paths. This is important because acoustic measurements are sensitive to background noise and simulated real-world measurements are typically performed in noisy rooms or environments, for example, a kitchen or train station. Calibrated measurements allow us to measure the noise floor and set the speaker level accordingly for accurate RT60 measurements. Plus, if you’re serious about smart device measurements you probably already have SoundCheck, so it makes sense to keep everything in the same test environment.

Let’s take a look. Here we have a Bruel & Kjaer omnidirectional sound source. These speakers are all connected in parallel to radiate sound evenly and in-phase in all directions. We’re going to capture the sound with 4 of our own SCM microphones, connected to the AmpConnect 621 audio interface which has 6 input and 2 output channels. The test sequence (which is available free of charge on our website) plays a continuous sine sweep out of the omnidirectional sound source and the room response is recorded with the four microphones. This test signal has excellent noise immunity and it’s easy to separate the fundamental from the harmonics to minimize distortion effects on the measurements. Room acoustics values are then determined using a backwards integrated impulse response method. This method is very fast and requires just one measurement at each location. The results from the four microphones are averaged and displayed as single lines on the graph for T20, T30 and T60 measurements, as well as all 3 clarity curves.

If you’d like to learn more about this optional module, or download the test sequence, visit our website, www.listeninc.com.