我一直在尝试使用fft实时获取声音频率（数字），并且我遇到了运行时错误。任何人都可以帮忙吗？
package com.example.recordsound;
import edu.emory.mathcs.jtransforms.fft.DoubleFFT_1D;
import ca.uol.aig.fftpack.RealDoubleFFT;
public class MainActivity extends Activity implements OnClickListener{
int audioSource = MediaRecorder.AudioSource.MIC; // Audio source is the device MIC
int channelConfig = AudioFormat.CHANNEL_IN_MONO; // Recording in mono
int audioEncoding = AudioFormat.ENCODING_PCM_16BIT; // Records in 16bit
private DoubleFFT_1D fft; // The fft double array
private RealDoubleFFT transformer;
int blockSize = 256; // deal with this many samples at a time
int sampleRate = 8000; // Sample rate in Hz
public double frequency = 0.0; // the frequency given
RecordAudio recordTask; // Creates a Record Audio command
TextView tv; // Creates a text view for the frequency
boolean started = false;
Button startStopButton;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
tv = (TextView)findViewById(R.id.textView1);
startStopButton= (Button)findViewById(R.id.button1);
}
@Override
public boolean onCreateOptionsMenu(Menu menu) {
// Inflate the menu; this adds items to the action bar if it is present.
getMenuInflater().inflate(R.menu.main, menu);
return true;
}
private class RecordAudio extends AsyncTask<Void, Double, Void>{
@Override
protected Void doInBackground(Void... params){
/*Calculates the fft and frequency of the input*/
//try{
int bufferSize = AudioRecord.getMinBufferSize(sampleRate, channelConfig, audioEncoding); // Gets the minimum buffer needed
AudioRecord audioRecord = new AudioRecord(audioSource, sampleRate, channelConfig, audioEncoding, bufferSize); // The RAW PCM sample recording
short[] buffer = new short[blockSize]; // Save the raw PCM samples as short bytes
// double[] audioDataDoubles = new double[(blockSize*2)]; // Same values as above, as doubles
// -----------------------------------------------
double[] re = new double[blockSize];
double[] im = new double[blockSize];
double[] magnitude = new double[blockSize];
// ----------------------------------------------------
double[] toTransform = new double[blockSize];
tv.setText("Hello");
// fft = new DoubleFFT_1D(blockSize);
try{
audioRecord.startRecording(); //Start
}catch(Throwable t){
Log.e("AudioRecord", "Recording Failed");
}
while(started){
/* Reads the data from the microphone. it takes in data
* to the size of the window "blockSize". The data is then
* given in to audioRecord. The int returned is the number
* of bytes that were read*/
int bufferReadResult = audioRecord.read(buffer, 0, blockSize);
// Read in the data from the mic to the array
for(int i = 0; i < blockSize && i < bufferReadResult; i++) {
/* dividing the short by 32768.0 gives us the
* result in a range -1.0 to 1.0.
* Data for the compextForward is given back
* as two numbers in sequence. Therefore audioDataDoubles
* needs to be twice as large*/
// audioDataDoubles[2*i] = (double) buffer[i]/32768.0; // signed 16 bit
//audioDataDoubles[(2*i)+1] = 0.0;
toTransform[i] = (double) buffer[i] / 32768.0; // signed 16 bit
}
//audiodataDoubles now holds data to work with
// fft.complexForward(audioDataDoubles);
transformer.ft(toTransform);
//------------------------------------------------------------------------------------------
// Calculate the Real and imaginary and Magnitude.
for(int i = 0; i < blockSize; i++){
// real is stored in first part of array
re[i] = toTransform[i*2];
// imaginary is stored in the sequential part
im[i] = toTransform[(i*2)+1];
// magnitude is calculated by the square root of (imaginary^2 + real^2)
magnitude[i] = Math.sqrt((re[i] * re[i]) + (im[i]*im[i]));
}
double peak = -1.0;
// Get the largest magnitude peak
for(int i = 0; i < blockSize; i++){
if(peak < magnitude[i])
peak = magnitude[i];
}
// calculated the frequency
frequency = (sampleRate * peak)/blockSize;
//----------------------------------------------------------------------------------------------
/* calls onProgressUpdate
* publishes the frequency
*/
publishProgress(frequency);
try{
audioRecord.stop();
}
catch(IllegalStateException e){
Log.e("Stop failed", e.toString());
}
}
// }
return null;
}
protected void onProgressUpdate(Double... frequencies){
//print the frequency
String info = Double.toString(frequencies[0]);
tv.setText(info);
}
}
@Override
public void onClick(View v) {
// TODO Auto-generated method stub
if(started){
started = false;
startStopButton.setText("Start");
recordTask.cancel(true);
} else {
started = true;
startStopButton.setText("Stop");
recordTask = new RecordAudio();
recordTask.execute();
}
}
}
当我运行该程序时，OnClick崩溃了 我为fft尝试了两个库，但是一次运行一个库以查看库是否正常工作 一旦到达我将块大小分配给FFT对象的行，它就会崩溃 任何人都可以提供帮助
答案 0 :(得分：12)
试试这个FFT：
public class FFT {
int n, m;
// Lookup tables. Only need to recompute when size of FFT changes.
double[] cos;
double[] sin;
public FFT(int n) {
this.n = n;
this.m = (int) (Math.log(n) / Math.log(2));
// Make sure n is a power of 2
if (n != (1 << m))
throw new RuntimeException("FFT length must be power of 2");
// precompute tables
cos = new double[n / 2];
sin = new double[n / 2];
for (int i = 0; i < n / 2; i++) {
cos[i] = Math.cos(-2 * Math.PI * i / n);
sin[i] = Math.sin(-2 * Math.PI * i / n);
}
}
public void fft(double[] x, double[] y) {
int i, j, k, n1, n2, a;
double c, s, t1, t2;
// Bit-reverse
j = 0;
n2 = n / 2;
for (i = 1; i < n - 1; i++) {
n1 = n2;
while (j >= n1) {
j = j - n1;
n1 = n1 / 2;
}
j = j + n1;
if (i < j) {
t1 = x[i];
x[i] = x[j];
x[j] = t1;
t1 = y[i];
y[i] = y[j];
y[j] = t1;
}
}
// FFT
n1 = 0;
n2 = 1;
for (i = 0; i < m; i++) {
n1 = n2;
n2 = n2 + n2;
a = 0;
for (j = 0; j < n1; j++) {
c = cos[a];
s = sin[a];
a += 1 << (m - i - 1);
for (k = j; k < n; k = k + n2) {
t1 = c * x[k + n1] - s * y[k + n1];
t2 = s * x[k + n1] + c * y[k + n1];
x[k + n1] = x[k] - t1;
y[k + n1] = y[k] - t2;
x[k] = x[k] + t1;
y[k] = y[k] + t2;
}
}
}
}
}
它应该解决你的想法。如果您决定重复使用它，请向作者提供适当的信用。
来源/作者：EricLarch
答案 1 :(得分：5)
如果您真的想要执行实时音频分析，那么基于Java的方法就无法做到。我在2013年第四季度为我的公司做了类似的任务，我们决定使用Kiss FFT（也许是最简单的带有BSD许可证的FFT库），使用NDK为Android编译。
本机C / C ++方法比Java对应方法吨快。使用前者，我们几乎可以在每个中高端设备上执行实时音频解码和音频功能分析，后者显然是不可能的
我强烈建议您将原生方法视为执行此任务的最佳选择。 Kiss FFT是一个非常简单的库（字面意思是Keep It Simple FFT），你在Android上编译和使用它时不会遇到太多麻烦。你不会对表现结果感到失望。
答案 2 :(得分：0)
你解决了这个问题吗？由于ArrayIndexOutOfBoundsException而发生了压缩。
因此，请将您的代码修改为：
double[] re = new double[blockSize];
double[] im = new double[blockSize];
double[] magnitude = new double[blockSize];
// Calculate the Real and imaginary and Magnitude.
for(int i = 0; i < blockSize+1; i++){
try {
// real is stored in first part of array
re[i] = toTransform[i * 2];
// imaginary is stored in the sequential part
im[i] = toTransform[(i * 2) + 1];
// magnitude is calculated by the square root of (imaginary^2 + real^2)
magnitude[i] = Math.sqrt((re[i] * re[i]) + (im[i] * im[i]));
}catch (ArrayIndexOutOfBoundsException e){
Log.e("test", "NULL");
}
}
double peak = -1.0;
// Get the largest magnitude peak
for(int i = 0; i < blockSize; i++){
if(peak < magnitude[i])
peak = magnitude[i];
}
// calculated the frequency
frequency = Double.toString((sampleRate * peak)/blockSize);