In this short video, Cam Ruffle-Deignan walks you through how to predict listener preference based on the Harman Target Curve. This free sequence (which can be downloaded here) can recall previously saved data as well as capture new data, making this a great ‘work from home’ project if you have previously saved measurement data on your headphones.
The Harman Target Curve is used to predict listener preference of headphones
In their landmark papers “A Statistical Model that Predicts Listeners’ Preference Ratings of In Ear Headphones – Parts 1&2” presented at the AES 143rd in October 2017, Sean E. Olive, Todd Welti, and Omid Khonsaripour of Harman International introduced a model that predicted listener preference ratings of headphones based on the Harman Target Curve. We have created a SoundCheck sequence that measures any headphones and predicts the listener preference rating based on comparing its measured results to the Harman Target curve using this model. Listen acknowledges and thanks the authors of the Harman paper for providing the spreadsheet which is used as the basis for the excel template used in this sequence.
This sequence, inspired by the Harman research referenced above, 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.
Check out our short video where we demonstrate this sequence in action
Get the test sequence for predicting headphone preference based on Harman Target Curves
Learn more about headphone testing using SoundCheck
References
A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 1—Listening Test Results and Acoustic Measurements
A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 2—Development and Validation of the Model
A Statistical Model that Predicts Listeners’ Preference Ratings of Around-Ear and On-Ear Headphones
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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