android getting sound frequencies real time?

Question

I have been trying to get the sound frequency(number) in real time using fft and i am having run time errors. can any one help?

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();
       }

}

}

AS SOON AS I run the program with the OnClick it crashes I tried two libraries for fft but ran one at a time to see if the library works or not As soon as it reaches the line where I assign the the block size to the FFT object it crashes can any one help

Answer 1

Did you solved the problem? The crush is occurred because of the ArrayIndexOutOfBoundsException.

So, modify your code to :

                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);

Answer 2

Try this 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;
              }
          }
      }
  }
}

It should address what you have in mind. If you decided to re-use it, give the proper credit to the author.

Source/Author: EricLarch

Answer 3

If you really want to perform a real-time audio analysis, a Java-based approach won't do. I had a similar task in Q4 2013 for my company, and we decided to use Kiss FFT (perhaps the most simple FFT library with a BSD license), compiled for Android using the NDK.

A native C/C++ approach is tons of times faster than its Java counterpart. With the former, we have been able to perform real-time audio decoding and audio features analysis on nearly every mid to high end device, something that was obviously impossible with the latter.

I strongly suggest you to consider the native approach as your best option to do this task. Kiss FFT is a really simple library (literally stands for Keep It Simple FFT), and you won't find much troubles in compiling and using it on Android. You won't be disappointed by the performance results.