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I'm thinking of starting a android project, which records audio signals and does some processing to denoise. My quesion is, as many (nearly all) denoising algorithms involve FFT, is it possible for me to do a real-time program? By real-time I mean the program do recording and processing at the same time, so I could save my time when I finish recording.

I have made a sample project, which applies fourier transformation to the audio signal and implement a simple algorithm called sub-spectrum. But I found that it is difficult to implement this algorithm in real time, which means after I press the 'stop' button, it takes me a while to do the processing and save the file (I'm also wondering how do these commercial recorder programs record sound and at the same time save it). I know that my FFT may not be the fastest, but I'd like to know whether I could achieve 'real-time', if I fully optimized it or use the fastest FFT code? Thanks a lot!

Shannon Matthews
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  • FFT stands for 'Fast Fourier Transform', so by definition it should be one of your faster options. One way to make it faster would be to decrease the size of the FFT, though this also decreases the quality. – David K May 13 '13 at 12:42

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It sounds like you are talking about broadband denoising. So I'll address my question to that. There are other kinds of denoising, from simple filtering to adaptive filtering to dynamic range expanding and probably others.

I don't think anyone can answer this question with a simple yes or no. You will have to try it and see what can be done.

First off, there are a variety of FFT implementations, including FFTW, of varying speed you could try. Some are faster than others, but at the end of the day they are all going to deliver comparable results.

This is one place where native C/C++ will outperform Java/Dalvik code because it can truly take advantage of vector code. For that to work, you'll probably need to write some assembler, or find some code that is already android optimized. I'm not aware of an android optimized FFT, but I'm sure it exists.

The real performance win will come from how you structure your overall denoising algorithm. All denoising I'm familiar with is extremely processor intensive and probably won't work on a phone in real-time, although it might on a tablet. That's just a(n educated) guess, though.

Bjorn Roche
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