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Try a basic pre-emphasis filter, as suggested, boosting the mid-to-high frequencies of the speech signal. This may work depending on the spectro-temporal characteristics of the noise.


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Can you provide more details about the context? What speech recognition system are you using? Can you add code to it? What type of background noise? A simple approach would be to add a pre-emphasis filter. A better approach would be to add a second microphone to capture background noise and then remove it.


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Human voice has the same frequencies as other noises, it is not possible to filter it with dumb algorithm. It is possible to filter based on temporal patterns like spectral subtraction, but this way you can only filter static noise, not background speech/bable noise. Pocketsphinx already has spectral subtraction. To filter noise reliably you need an ...


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