I've been looking into improving AI models for speech recognition in noisy environments, which could have benefits for hearing-impaired microphone technology. It's challenging but crucial for many sets of real-world applications. Are there any audio-processing experts here? How do you approach noise reduction and speaker separation in your models?

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https://www.bbc.com/news/articles/c5yk5mdj9gxo

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Could you give a TLDR of the article?

Not really an audio expert, but I do something sort of similar for video games. I can never hear people running up on me, so I built a software device that takes Dolby 7.1 and filters my own noise, sounds that are less important. The result is I can hear someone crouch walking three houses away. Footsteps are kinda hard to isolate similar to your issue. Once you isolate the sound you want you can play with microphone input threshold to filter out background noise. Take a look at voice meter and APO Equalizer on Windows to do something similar. That might help you prove out a concept.

Background noise isolation isn’t really a new thing though plantronic headsets have always done a great job. You can add frequency filters quite easily if you can solder. Maybe figure it out with software, then try to replicate with physical hardware and filters. I’ve only done frequency filters for like subwoofers, car stereos. Too cheap to buy an Equalizer. If you could use out of the box hardware even better.

Please build me something that translates languages in realtime in both directions that isn’t clunky. Language really shouldn’t be a barrier.

Thanks for sharing!

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