对音频信号实施高通滤波器

我能够编写一个程序来捕获音频信号，消除背景噪音，应用窗口函数和信号可视化。 我的程序正在努力到这一点，没有错误。 现在我正在尝试对我的代码实现高通滤波器。 我已经为这部分找到了一个API。 但我根据我的代码无法应用它。 这是我的代码：

private class RecordAudio extends AsyncTask { @Override protected Void doInBackground(Void... params) { started = true; try { DataOutputStream dos = new DataOutputStream( new BufferedOutputStream(new FileOutputStream( recordingFile))); int bufferSize = AudioRecord.getMinBufferSize(frequency, channelConfiguration, audioEncoding); audioRecord = new AudioRecord(MediaRecorder.AudioSource.MIC, frequency, channelConfiguration, audioEncoding, bufferSize); NoiseSuppressor.create(audioRecord.getAudioSessionId()); short[] buffer = new short[blockSize]; double[] toTransform = new double[blockSize]; long t = System.currentTimeMillis(); long end = t + 15000; audioRecord.startRecording(); while (started && System.currentTimeMillis() < end) { int bufferReadResult = audioRecord.read(buffer, 0, blockSize); for (int i = 0; i < blockSize && i < bufferReadResult; i++) { toTransform[i] = (double) buffer[i] / 32768.0; dos.writeShort(buffer[i]); } toTransform = hann(toTransform); transformer.ft(toTransform); publishProgress(toTransform); } audioRecord.stop(); dos.close(); } catch (Throwable t) { Log.e("AudioRecord", "Recording Failed"); } return null; } 

这是API链接。

任何人都可以帮我做这个function吗？ 我真的很感激！ 🙂

提前致谢！

Answer 1

这是我从c＃中找到的库转换为java的类。 我用它，效果很好。 您也可以将此类用于低通滤波器

 public class Filter { /// 
 /// rez amount, from sqrt(2) to ~ 0.1 /// 
 private float resonance; private float frequency; private int sampleRate; private PassType passType; public float value; private float c, a1, a2, a3, b1, b2; /// 
 /// Array of input values, latest are in front /// 
 private float[] inputHistory = new float[2]; /// 
 /// Array of output values, latest are in front /// 
 private float[] outputHistory = new float[3]; public Filter(float frequency, int sampleRate, PassType passType, float resonance) { this.resonance = resonance; this.frequency = frequency; this.sampleRate = sampleRate; this.passType = passType; switch (passType) { case Lowpass: c = 1.0f / (float)Math.tan(Math.PI * frequency / sampleRate); a1 = 1.0f / (1.0f + resonance * c + c * c); a2 = 2f * a1; a3 = a1; b1 = 2.0f * (1.0f - c * c) * a1; b2 = (1.0f - resonance * c + c * c) * a1; break; case Highpass: c = (float)Math.tan(Math.PI * frequency / sampleRate); a1 = 1.0f / (1.0f + resonance * c + c * c); a2 = -2f * a1; a3 = a1; b1 = 2.0f * (c * c - 1.0f) * a1; b2 = (1.0f - resonance * c + c * c) * a1; break; } } public enum PassType { Highpass, Lowpass, } public void Update(float newInput) { float newOutput = a1 * newInput + a2 * this.inputHistory[0] + a3 * this.inputHistory[1] - b1 * this.outputHistory[0] - b2 * this.outputHistory[1]; this.inputHistory[1] = this.inputHistory[0]; this.inputHistory[0] = newInput; this.outputHistory[2] = this.outputHistory[1]; this.outputHistory[1] = this.outputHistory[0]; this.outputHistory[0] = newOutput; } public float getValue() { return this.outputHistory[0]; } } 

这就是我使用它的方式

  Filter filter = new Filter(15000,44100, Filter.PassType.Highpass,1); for (int i = 0; i < numSamples; i++) { filter.Update(floatArray[i]); floatArray[i] = filter.getValue(); } 

在你获得了floatArray的fft后，你会看到它被过滤了。 希望能帮助到你