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Microphone Polar Plot Substitution Method Using Outline ET250-3D

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This sequence measures the directional response of a microphone and graphs the result as a polar plot. A log sweep stimulus is played from 100 Hz to 10 kHz at each angular increment, and the acquired waveform is analyzed using the Time Selective Response algorithm. This method allows the test to be performed in a non-anechoic environment by placing a window around the direct signal, eliminating the influence of reflections. Commands are sent automatically to the Outline ET250-3D turntable via an ethernet connection, instructing it to move in 10 degree increments after each measurement. The sequence measures the response every 10 degrees from 0 to 180 and mirrors the polar image, which simulates a full 360 degree polar and saves test time. The response at each angular increment is compared against the on-axis response to create a normalized curve. This removes the influence of the device’s frequency response and sensitivity, such that the polar plot only shows the directional response. The final display also contains a graph of the directivity index in decibels versus frequency.

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RT60 Room Acoustics

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The RT60 room acoustics sequence measures reverberation time and clarity of a room using multiple microphones to accurately characterize measurement environments. This is important for smart device testing as measurements of both speech recognition and audio output often need to be made in fully characterized rooms with known reverberation times and clarity. The method used in this sequence is fast, accurate, and made using fully calibrated signal paths. This sequence uses an omnidirectional speaker to play a Log Sweep from 250Hz – 15kHz and four microphones measure the impulse responses generated. These waveforms are analyzed using the Time Selective Response and room acoustics algorithms to calculate reverberation time (T20, T39, T60) and clarity (C7, C50 and C80) according to ISO 3382-1:2009.
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Prediction of Listener Preference of In-Ear Headphones (Harman Model)

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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, on-ear and over-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. The sequence also provides the option to recall data rather than making a measurement, which saves time for engineers who already have large quantities of saved data, and enables historical comparison with obsolete products.

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Measuring Max SPL versus Frequency

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This sequence measures the Max SPL of a transducer versus frequency that a device can play back with acceptable distortion. It is particularly valuable for designers using DSP algorithms to optimize the performance of their speakers.

It characterizes the Max SPL of a transducer by setting limits on specific metrics (THD, Rub & Buzz, Perceptual Rub & Buzz, Input Voltage and Compression) and then driving the transducer at a series of standard ISO frequencies, increasing the stimulus level until the one of the limits is surpassed. The sequence begins by measuring the frequency response and impedance of the DUT. The user is asked if they wish to use the -3dB from resonance frequency as the test Start Frequency or manually enter another value. The user is then prompted to enter a Stop Frequency, initial test level and limit values for the metrics of interest. The sequence then plays the stimulus Start Frequency in a loop, increasing the level +3dB with each loop iteration until one of the limits is exceeded.  The stimulus level is then adjusted -3dB and the sequence continues to a second loop which increases the stimulus level +0.5 dB with each loop iteration until the limit is exceeded. At this point, the limit results are saved to an Excel file, the stimulus frequency is incremented by a constant multiplication step and the process is repeated until the Stop Frequency is achieved. Every time the main loop is completed, the individual SPL and Stimulus Level x-y pairs are concatenated to master curves. At the end of the sequence, the Max SPL and Stimulus Level curves are autosaved in .dat format.

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Smart Speaker – Embedded Microphone Test Sequence

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smart_speaker_final_display_micThis sequence demonstrates a method by which SoundCheck can measure the performance of a microphone 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 WAV file (“Alexa”) with one specific to the desired make and model.

The sequence begins by playing a voice activation phrase out of a source speaker, prompting the DUT to record both the voice command and the ensuing stepped sine sweep stimulus. A message step then prompts the operator to retrieve this recording from the DUT’s cloud storage system. This is accomplished by playing back the recording from the cloud and capturing it with a Triggered Record step in the SoundCheck test sequence.  The Recorded Time Waveform is then windowed (to remove the voice command) and frequency shifted prior to analysis and the result (Frequency Response) is shown on the final display step.

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Smart Speaker – Embedded Loudspeaker Test Sequence

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smart_speaker_final_displayThis 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.

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Headphone Testing with SoundCheck ONE

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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.

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IEC-60268-7 Headphone Sequences

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IEC-60268-7: Sound System Equipment – Part 7: Headphones and Earphones is an international standard intended to characterize the performance of headphones and earphones. The standard itself is a lengthy document, 9 Sections and 3 Annexes covering 46 printed pages. These SoundCheck sequences focus on the electro-acoustic tests which are detailed in Section 8 “Characteristics to be specified and their method of measurement”.

Five separate sequences are provided, each designed to measure specific characteristics. This approach provides the user with the flexibility to measure all or some of the characteristics of their headphone.

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Advanced Sequence Development

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Expand the capabilities of your test sequences by learning how to implement advanced functions such as conditional branching, looping, and sub-sequencing. Presented by Brian Fallon, Listen, Inc. Status: Recorded. Watch Webinar