First of all, thank you for having a cordial discussion about this. I very much appreciate this type of conversation and I value hearing your opinion on this. It’s hard to have this type of discussion unless it’s with somebody who’s already taken the time to review the video and read the article in-depth to know what Oticon is talking about and form their own opinion about it. And not everybody has the time or want to bother spending the time to understand more about the topic, which is fine because life is too busy for everyone, and also the material is quite in-depth and technical.
I think you probably misunderstand when you think that I’m saying that the OPN is better at noise reduction, and understandably so because I did use the word TRUE in capital when referring to the OPN type of noise reduction, causing this impression. So I apologize if it was taken the way I didn’t mean to. I actually think either approach can work, as I already said later on in my later posts on this thread. I think it highly depends on the individual and their brain hearing ability as to which approach works better for them, so it’s a personal decision, really. That’s why I don’t go around telling people that the OPN is the be-all-end-all of hearing aids in every thread, although some folks may get that impression from reading my posts, even though I never said those words. In the context of this thread, the OP said his HAs don’t work for him in restaurants, asked for inputs on what else he can try. So I thought that the OPN with its new paradigm is different enough that it’d be something worth trying. I could have simply said try the OPN and be done with it. But I wanted to provide a context on why I think the OPN may help because of how it’s different from other HAs in its new approach. But apparently my detailed post seems to have rubbed some people the wrong way because it came across as promoting the OPN to be superior, while all I meant is that the OPN is different, although I still truly think different in a very good way based on my personal experience.
Now, having said that, let’s get back to the noise reduction discussion. I think it comes down to how you define noise reduction, and what noise is, and what speech is. And you’re right that what Oticon does is clever beam forming, and obviously traditional directional HAs do beam forming, too, so what’s the difference? While we both agree, and so does Oticon on the OPN and other mfgs in their implementation, that noise is defined as what’s behind you and speech as what’s in front of you, the approach to removing noise is completely different, even though both approaches utilizes beam forming in a way. The traditional beam forming removes noise from behind simply by virtue of picking up sound from the front only. But it doesn’t do anything further to the sound it picks up from the front. And the dilemma with this is that there is still noise combined with speech in the sound coming from the front. Granted, there’s less information now coming only from the front, which can help people focus better instead of having to deal with ALL the sound from all around. But the front sound is still polluted with noise, so people at this point will have to manually do this speech and noise separation with their own brain hearing power. Many people can do this successfully, but apparently there are people who can’t (like our OP).
This is what the Oticon video seminar is trying to explain, on how they can take this one step further and try to clean up this polluted front sound. And this is where the Oticon’s approach to noise removal goes beyond just clever beam forming. They do this by breaking out the sound spectrum into 16 frequency bands, take samples in each band and compare the sound average between their front sound and their rear sound (which is used as the noise model), and if they detect that the sound average of the rear sound is higher than that of the front sound, that implies that the rear noise is drowning out the front speech, so they reduce the rear noise by either 3db or 6db or 9db in that frequency band, depending on the settings of low or medium or high noise reduction level (also limited by the different models, as the Opn3 can only reduce up to 3db, Opn2 by 6db, and Opn1 anywhere between 3 to 9 db). This is where the processing speed comes in and can make a difference. If your processing speed is not fast enough, your sample is a longer term average. If your processing speed is fast enough, your sample is a shorter term average. Oticon is saying that on the whole, long term averages of the 2 sound sources (rear noise and front sound) almost always look virtually identical, so you can’t see enough differences in order to help you decide which of the 16 frequency bands you need to reduce gain on and which ones to leave the gain alone to execute your noise removal strategy. But if you can keep drilling down to shorter and shorter term average samples, you’ll begin to see discernible differences between the rear noise and the front sound to help you remove the rear noise. In order to drill down to very short enough sample average, you need to have faster processing speed. That’s where the OPN faster Velox platform comes in, with enough processing speed to enable them to execute this strategy.
And this is why I call it TRUE noise reduction, because this strategy can actually take that next step and actually also help remove the noise from the polluted front sound, while traditional beam forming doesn’t do this. I now realize that this choice of word might have irked many folks, so I’m OK with just calling it FRONT noise reduction to be more politically correct. But to me, noise reduction is not about blocking out sounds out completely in certain areas and pick up sounds from other area, that’s actually just beam forming. To me, noise reduction is actually about going into the polluted signal and figure out a way to remove the pollution from that signal. That’s more than just beam forming.
Some folks reading this may wonder if Oticon’s approach using beam forming AND noise reduction here is inconsistent with its open paradigm or not. After all, aren’t you supposed to hear everything everywhere? What if there’s speech coming from behind? Is that considered noise? In the OpnSound Navigator white paper on page 5, they talk about a Voice Activity Detector that operates independently in each of the 16 frequency bands and is used to detect speech that are not coming from the front and freeze the noise removal module to preserve this speech coming from the rear. So at least it seems like they’ve thought about this situation and have a way to manage it. Also, this type of noise removal from speech only happens on a moment to moment basis (up to 100 times/moments per second). But as soon as speech is no longer detected, all noise from everywhere is let through again. So there’s NO steady state noise reduction in the OPN strategy, only moment to moment noise reduction, and only on clearly defined speech.
This lack of steady state noise reduction is what irked me THE MOST when I originally started wearing the OPN. I was used to having this steady state noise reduction on my old HAs (by virtue of directionally blocking out sound), so not having it on the OPN bothered me a lot. But after about a month of wearing the OPN, my brain adjusted and now it just naturally tunes out those steady state noises, so they don’t bother me anymore. In hindsight, that’s actually part of the big plan, to let all sound and noise come through and let your brain decide what’s to tune out and what’s to focus on. After all, noise IS sound, so the definition of real noise is very subjective anyway and no HA in the world can read your mind to know what’s sound and what’s noise to YOU. Even to yourself, noise can also vary from situation to situation. For example, if you walk on the sidewalk, passing by cars may be considered noise by you. But if you decide to cross the street, all of a sudden, car noise becomes crucial to your safety and is not noise anymore. For this reason, the OPN and its new open paradigm just lets all the sounds through, and the only place it wants to try to help is with noise removal if there’s speech coming from the front. The end result is that you may hear clearer speech in front, but as soon as speech stops, you hear everything again, noise included, whether you like it or not.