Home » Android » android – How many FFTs per second can I do on my smartphone? (for performing voice recognition)

# android – How many FFTs per second can I do on my smartphone? (for performing voice recognition)

Questions:

I’m exploring voice recognition and DSP, and so I would like to implement a simple sound frequency analyzer on my smartphone (I have both an iPhone and a Samsung Nexus S running Android). I have done basic DSP in Matlab previously.

From my understanding, I need to perform an FFT to get the fundamental frequencies of a signal.

So now, I would like to sample the microphone at 44100 Hz. If I use a sliding window of sample size 512 with 50% overlap, that means I need to do an FFT every 256 samples, or 0.00580 seconds.

That rate seems really high, particularly if I program in Java for Android. Will my smartphone be able to handle that speed? I am aware that you can program in C/C++ on Android, but I would like to keep it with Java for the time being.

Performing a real-to-complex FFT requires ~5/2 n lg n floating-point operations (additions and multiplications). In your case, n=512, so:

``````flops per fft ~= (5/2) * 512 * 9 = 11520
``````

So 172 ffts per second requires about 2 million floating-point operations per second. That sounds like a lot, but it really isn’t that many. The hardware of a typical armv7-class smartphone is capable of hundreds of millions or billions of floating-point operations per second.

Note however that you will want to have a carefully-written high-performance FFT; poorly written FFTs are notoriously inefficient. On the iPhone, you can use the Accelerate framework (built right into the OS, and available in the SDK), which provides a nice set of FFT functions; I’m not sure what’s available on Android.

For the iPhone, the Accelerate framework for iOS can do all the FFTs you specify using on the order of 1% of CPU time (exact percentage depending on device model and FFT data types).

For Android, you might strongly want to consider using an NDK native library for processor intensive numerical calculations.

Also note that an FFT will give you the peak frequencies, which will not necessarily include the fundamental or voice pitch frequency.

ADDED: This Java benchmark web page suggests that Android phones are capable of in the range of 5 to over 50 MFlops using Java for well written matrix math. A well written FFT should fall around roughly the same performance range in MFlops. @Stephan Cannon posted that on the order of 2 MFlops might be required for your spec.