什么可能导致FFT数据在错误的频率上出现尖峰？

Question

我使用的是苹果的加速框架,讨论了关于iPhone执行FFT间距检测很多 次这里之前.

我理解相位偏移,bin频率,并且已经研究了几种使用FFT技术(简单音调检测,自相关,倒谱等)来检测音调的开源调谐器.这是我的问题:

我的FFT结果始终偏离5-10 Hz(+/-),即使这些箱仅相隔1-2赫兹.我尝试过不同的算法,即使是以高分辨率采样的简单FFT也会显示出看似错误的地方的幅度峰值.这不是一致的偏移; 有些太高,有些太低.

例如,440Hz的音调为445.2 Hz; 220Hz为214Hz; 880Hz为874Hz; 使用音调发生器,1174Hz为1183Hz.使用几乎完全相同的算法的Mac 类似的开源调谐器没有问题完美地检测音调.(这些差异在设备上与模拟器不同,但它们仍处于关闭状态.)

我不认为问题是分辨率,因为实际音调和检测到的幅度尖峰之间通常有几个分档.好像输入只是听错了音调.

我在下面粘贴了我的代码.一般流程很简单:

向FFT缓冲区推进一步 - > Hann窗口 - > FFT - >相位/幅度 - >最大间距错误.

enum {
    kOversample = 4,
    kSamples = MAX_FRAME_LENGTH,
    kSamples2 = kSamples / 2,
    kRange = kSamples * 5 / 16,
    kStep = kSamples / kOversample
};



const int PENDING_LEN = kSamples * 5;
static float pendingAudio[PENDING_LEN * sizeof(float)];
static int pendingAudioLength = 0;

- (void)processBuffer {
    static float window[kSamples];
    static float phase[kRange];
    static float lastPhase[kRange];
    static float phaseDeltas[kRange];
    static float frequencies[kRange];
    static float slidingFFTBuffer[kSamples];
    static float buffer[kSamples];

    static BOOL initialized = NO;
    if (!initialized) {
        memset(lastPhase, 0, kRange * sizeof(float));

        vDSP_hann_window(window, kSamples, 0);
        initialized = YES;
    }

    BOOL canProcessNewStep = YES;
    while (canProcessNewStep) {        

        @synchronized (self) {
            if (pendingAudioLength < kStep) {
                break; // not enough data
            }            
            // Rotate one step's worth of pendingAudio onto the end of slidingFFTBuffer
            memmove(slidingFFTBuffer, slidingFFTBuffer + kStep, (kSamples - kStep) * sizeof(float));
            memmove(slidingFFTBuffer + (kSamples - kStep), pendingAudio, kStep * sizeof(float));
            memmove(pendingAudio, pendingAudio + kStep, (PENDING_LEN - kStep) * sizeof(float));
            pendingAudioLength -= kStep;   
            canProcessNewStep = (pendingAudioLength >= kStep);
        }

        // Hann Windowing
        vDSP_vmul(slidingFFTBuffer, 1, window, 1, buffer, 1, kSamples);      
        vDSP_ctoz((COMPLEX *)buffer, 2, &splitComplex, 1, kSamples2);        

        // Carry out a Forward FFT transform.
        vDSP_fft_zrip(fftSetup, &splitComplex, 1, log2f(kSamples), FFT_FORWARD);        

        // magnitude to decibels
        static float magnitudes[kRange];        
        vDSP_zvmags(&splitComplex, 1, magnitudes, 1, kRange);        
        float zero = 1.0;
        vDSP_vdbcon(magnitudes, 1, &zero, magnitudes, 1, kRange, 0); // to decibels

        // phase
        vDSP_zvphas(&splitComplex, 1, phase, 1, kRange); // compute magnitude and phase        
        vDSP_vsub(lastPhase, 1, phase, 1, phaseDeltas, 1, kRange); // compute phase difference
        memcpy(lastPhase, phase, kRange * sizeof(float)); // save old phase

        double freqPerBin = sampleRate / (double)kSamples;
        double phaseStep = 2.0 * M_PI * (float)kStep / (float)kSamples;

        // process phase difference ( via https://stackoverflow.com/questions/4633203 )
        for (int k = 1; k < kRange; k++) {
            double delta = phaseDeltas[k];
            delta -= k * phaseStep;  // subtract expected phase difference
            delta = remainder(delta, 2.0 * M_PI);  // map delta phase into +/- M_PI interval
            delta /= phaseStep;  // calculate diff from bin center frequency
            frequencies[k] = (k + delta) * freqPerBin;  // calculate the true frequency
        }               

        NSAutoreleasePool *pool = [[NSAutoreleasePool alloc] init];

        MCTunerData *tunerData = [[[MCTunerData alloc] initWithSize:MAX_FRAME_LENGTH] autorelease];        

        double maxMag = -INFINITY;
        float maxFreq = 0;
        for (int i=0; i < kRange; i++) {
            [tunerData addFrequency:frequencies[i] withMagnitude:magnitudes[i]];
            if (magnitudes[i] > maxMag) {
                maxFreq = frequencies[i];
                maxMag = magnitudes[i];
            }
        }

        NSLog(@"Max Frequency: %.1f", maxFreq);

        [tunerData calculate];

        // Update the UI with our newly acquired frequency value.
        [self.delegate frequencyChangedWithValue:[tunerData mainFrequency] data:tunerData];

        [pool drain];
    }

}

OSStatus renderCallback(void *inRefCon, AudioUnitRenderActionFlags *ioActionFlags, 
                       const AudioTimeStamp *inTimeStamp, UInt32 inBusNumber, UInt32 inNumberFrames, 
                       AudioBufferList *ioData)
{
    MCTuner* tuner = (MCTuner *)inRefCon;    

    OSStatus err = AudioUnitRender(tuner->audioUnit, ioActionFlags, inTimeStamp, 1, inNumberFrames, tuner->bufferList);
    if (err < 0) {
        return err;
    }

    // convert SInt16 to float because iOS doesn't support recording floats directly
    SInt16 *inputInts = (SInt16 *)tuner->bufferList->mBuffers[0].mData;

    @synchronized (tuner) {
        if (pendingAudioLength + inNumberFrames < PENDING_LEN) {

            // Append the audio that just came in into the pending audio buffer, converting to float
            // because iOS doesn't support recording floats directly
            for(int i = 0; i < inNumberFrames; i++) {
                pendingAudio[pendingAudioLength + i] = (inputInts[i] + 0.5) / 32767.5;
            }
            pendingAudioLength += inNumberFrames;
        } else {
            // the buffer got too far behind. Don't give any more audio data.
            NSLog(@"Dropping frames...");
        }
        if (pendingAudioLength >= kStep) {
            [tuner performSelectorOnMainThread:@selector(processBuffer) withObject:nil waitUntilDone:NO];
        }
    }

    return noErr;
}

Answer 1

我确信这实际上并不是我的算法中的任何内容；相反，我使用 Apple 的 AUGraph 时出了问题。当我删除它以仅使用普通音频单元而不设置图表时，我能够让它正确识别音高。