FFT 音频输入 [英] FFT audio input

问题描述

我想对由 AudioRecorder 记录并保存到 wav 文件的信号应用 FFT.我使用的 FFT 有一个 Complex[] 输入参数.我很困惑，从字节转换为复数除以 32768 与仅将虚部加 0 并将实部保留为字节进行转换是否有区别?

I want to apply FFT on a signal recorded by AudioRecorder and saved to a wav file. the FFT i am using has a Complex[] input parameter. I am confused, is there a difference between converting from bytes to comlex dividing by 32768, and converting by just adding 0 to the imaginary part and leaving the real part as a byte?

public Complex[] convertToComplex(byte[] file)
{


    int size= file.length;
    double[]x=new double[size];
    Complex[]data= new Complex[size];
    for(int i=0;i<size;i++)
    {
        x[i]=file[i]/32768.0;
        data[i]=new Complex(x[i],0);
        //  Log.d("tag", "indice"+i+":"+data[i]);
    }
    return data;
}

推荐答案

如果您正在处理位深度为 16 位的音频(每个样本有 16 位)，那么每个字节将只有一个样本的一半.什么您需要做的是将您的字节转换为 16 位样本，然后将结果数字除以 32768(这是 2 的补码 16 位数字可以存储的最小数字的大小，即 2^15)以获得实际的音频样本，这是一个-1 和 1 之间的数字.然后，您将通过将其虚部设置为 0 将该数字转换为复数.

If you are working with audio with a bit depth of 16 bits (each sample has 16 bits), then each byte will only have half of a sample.What you need to do is cast your bytes to 16 bit samples then divide the resulting number by 32768 (This is the magnitude of the smallest number a 2's complement 16 bit number can store i.e 2^15) to get the actual audio sample which is a number between -1 and 1.You will then convert this number to a complex number by setting it's imaginary component to 0.

可以在下面看到一个小的 C# 示例(指示性代码):

A small C# sample can be seen below (indicative code):

    byte[] myAudioBytes = readAudio();
    int numBytes = myAudioBytes.Length;

    var myAudioSamples = new List<short>();

    for( int i = 0; i < numBytes; i = i + 2)
    {
      //Cast to 16 bit audio and then add sample
       short sample = (short) ((myAudioBytes[i] << 8 | myAudioBytes[i + 1]) / 32768 ); 
       myAudioSamples.Add(sample);
    }

    //Change real audio to Complex audio

    var complexAudio = new Complex[myAudioSamples.Length];

    int i = 0;
    foreach(short sample in myAudioSamples)
       complexAudio[i++] = new Complex(){ Real = sample, Imaginary = 0 };

   //Now you can proceed to getting the FFT of your Audio here

希望代码能指导您如何处理音频.

Hope the code has guided you on how you should handle your audio.

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