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TWiRT 337 – Predicting Headphone Sound Quality with Sean Olive

The predicted sound quality of 61 different models of in-ear headphones (blue curve) versus their retail price (green bars).

On February 16, 2017 I was interviewed by host Kirk Harnack on This Week in Radio Tech. The topic was  “Predicting Sound Headphone Sound Quality”. You can find the interview here.

During the interview, Kirk asked if it’s possible to design a good sounding headphones for a reasonable cost. Or does one need to spend a considerable amount of cash to obtain good sound? Fortunately for consumers,   my answer was that you can get decent sound without having to spend thousands or even hundreds of dollars. In fact, there is almost no correlation between price and sound quality based on our research.
 I referred to the slide above that shows the predicted sound quality for 61 different models of in-ear headphones based on their measured frequency response.  The correlation between price and sound quality is close to zero and, slightly negative: r = -.16 (i.e. spending more money gets you slightly worse sound on average).

So, if you think spending a lot of money on in-ear headphones guarantees you will get excellent sound, you may be sadly disappointed. One of the most expensive IE models ($3000) in the above graph, had a underwhelming predicted score of 20-25% depending what EQ setting you chose. The highest scoring headphone was a $100 model that we equalized to hit the Harman target response, which our research has shown to be preferred by the majority of listeners.

The sound quality scores in the graph are predicted using a model based on a small sample of headphones that were evaluated by trained listeners in double-blind test. The accuracy of the model is better than 96% but limited to the small sample we tested.  We just completed a large listening test study involving over 30 models and 75 listeners that will allow us to build more accurate and robust predictive models. 
The ultimate goal of this research is to accurately predict the sound quality of headphones based on acoustic measurements without having to conduct expensive and time consuming listening tests. The current engineering approach to tuning headphones is clearly not optimal based on the above slide. Will headphone industry standards, headphone manufacturers and audio review magazines use similar predictive models to reveal to consumers how good the headphones sound?  What do you think?

TWiRT 337 – Predicting Headphone Sound Quality with Sean Olive

The predicted sound quality of 61 different models of in-ear headphones (blue curve) versus their retail price (green bars).

On February 16, 2017 I was interviewed by host Kirk Harnack on This Week in Radio Tech. The topic was  “Predicting Sound Headphone Sound Quality”. You can find the interview here.

During the interview, Kirk asked if it’s possible to design a good sounding headphones for a reasonable cost. Or does one need to spend a considerable amount of cash to obtain good sound? Fortunately for consumers,   my answer was that you can get decent sound without having to spend thousands or even hundreds of dollars. In fact, there is almost no correlation between price and sound quality based on our research.
 I referred to the slide above that shows the predicted sound quality for 61 different models of in-ear headphones based on their measured frequency response.  The correlation between price and sound quality is close to zero and, slightly negative: r = -.16 (i.e. spending more money gets you slightly worse sound on average).

So, if you think spending a lot of money on in-ear headphones guarantees you will get excellent sound, you may be sadly disappointed. One of the most expensive IE models ($3000) in the above graph, had a underwhelming predicted score of 20-25% depending what EQ setting you chose. The highest scoring headphone was a $100 model that we equalized to hit the Harman target response, which our research has shown to be preferred by the majority of listeners.

The sound quality scores in the graph are predicted using a model based on a small sample of headphones that were evaluated by trained listeners in double-blind test. The accuracy of the model is better than 96% but limited to the small sample we tested.  We just completed a large listening test study involving over 30 models and 75 listeners that will allow us to build more accurate and robust predictive models. 
The ultimate goal of this research is to accurately predict the sound quality of headphones based on acoustic measurements without having to conduct expensive and time consuming listening tests. The current engineering approach to tuning headphones is clearly not optimal based on the above slide. Will headphone industry standards, headphone manufacturers and audio review magazines use similar predictive models to reveal to consumers how good the headphones sound?  What do you think?

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