Inox Login - Login Individual on Sitemap.INOX Wind: When promoters put in money in troubled business, it calls for deeper look.Inox Wind Board approves merger of Inox Wind Energy Limited into the Company.Inox Wind’s 3 MW Wind Turbine receives certification.Inox Wind’s 3MW Turbine gets Type Certification from Germany, paves way for commercial launch.Inox Wind receives Type Certification from TUV SUD for its 3 MW wind turbine.Perhaps eventually some of those techniques will be scaled up past narrowband. That’s why all the development is happening in narrowband, because that’s the only interesting space left. Opus is so good there’s pretty much nothing left to improve for now ( for now), and even if you improved things it probably wouldn’t be worth it. ![]() Past about 16kb/s, Opus is pretty much just the format to use, except for extreme niches like if you want to represent over 20kHz (above which Opus cuts). especially shows Opus’ superiority except in narrowband. (audio_format) has some good diagrams and explanation. And in most cases the incumbents were high-latency, while Opus not only achieves quality superiority but also supports low-latency operation. Opus tackled a broad field of competitors that were each somewhat specialised for their part of the field, and pretty much beat all of them at their own game. The only areas where it’s being beaten are extreme narrowband, which it can’t do, and narrowband, where it’s still not shabby (though some of this new stuff is redefining what’s possible). Opus is a remarkable codec because it’s excellent at almost everything. It's also possible that "the algorithm said that" will be a common enough argument due to other factors (incorrect memory and increasing awareness of ML-based algorithms) that it'll out number the cases where it really happens. You need to record a local accurate copy, the receiver's processed copy, and know to look for it in what will likely be many hours of audio. But it'll be really hard to know that the recording doesn't record what was actually said. People have context (assuming they're actually listening, which is a whole other tier of hearing what you expect to hear) and people pick the wrong word or pronounce things incorrectly (as in not recognizable to the listener as what the speaker intended) all the time. which happens all the time because memory is incredibly lossy and maleable. They would have to listen to a recording some time later and detect that the recording doesn't match up with what they thought they said. Assume the user has somehow overcome the odd psychological effects that come hearing the computer generated audio played back, if that audio is mixed with what the person is already hearing, it's likely they still won't notice because they still hear themselves. The algorithm removes the ambiguity, but the listener can't tell because they hear themselves through their own sense of hearing. ![]() Perhaps they have one of the many ever evolving accents that almost certainly were not and absolutely could not possibly be included in the training set (ongoing vowel shifts might be a big cause of this). Suppose a person says something that the codec interprets differently. My last neuroscience class was many years ago, but I do remember that in some sense, we hear what we expect to hear (more so than vision if I recall correctly, though there is plenty that happens in our vision processing) in that our ears tune for particular frequencies to filter out ambiguities. ![]() I also expect this failure mode will be undetected for a long time due to how our sense of hearing works.
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