我想让我的Android应用识别声音。例如,我想知道麦克风发出的声音是拍手还是敲门声或别的东西。Android中的声音识别
我需要使用数学,还是我可以使用一些库?
如果有任何声音分析库,请告诉我。谢谢。
我想让我的Android应用识别声音。例如,我想知道麦克风发出的声音是拍手还是敲门声或别的东西。Android中的声音识别
我需要使用数学,还是我可以使用一些库?
如果有任何声音分析库,请告诉我。谢谢。
你不需要数学,你不需要AudioRecord。每隔1000毫秒检查MediaRecorder.getMaxAmplitude()。
以下是您需要的一些代码。
public class Clapper
{
private static final String TAG = "Clapper";
private static final long DEFAULT_CLIP_TIME = 1000;
private long clipTime = DEFAULT_CLIP_TIME;
private AmplitudeClipListener clipListener;
private boolean continueRecording;
/**
* how much louder is required to hear a clap 10000, 18000, 25000 are good
* values
*/
private int amplitudeThreshold;
/**
* requires a little of noise by the user to trigger, background noise may
* trigger it
*/
public static final int AMPLITUDE_DIFF_LOW = 10000;
public static final int AMPLITUDE_DIFF_MED = 18000;
/**
* requires a lot of noise by the user to trigger. background noise isn't
* likely to be this loud
*/
public static final int AMPLITUDE_DIFF_HIGH = 25000;
private static final int DEFAULT_AMPLITUDE_DIFF = AMPLITUDE_DIFF_MED;
private MediaRecorder recorder;
private String tmpAudioFile;
public Clapper() throws IOException
{
this(DEFAULT_CLIP_TIME, "/tmp.3gp", DEFAULT_AMPLITUDE_DIFF, null, null);
}
public Clapper(long snipTime, String tmpAudioFile,
int amplitudeDifference, Context context, AmplitudeClipListener clipListener)
throws IOException
{
this.clipTime = snipTime;
this.clipListener = clipListener;
this.amplitudeThreshold = amplitudeDifference;
this.tmpAudioFile = tmpAudioFile;
}
public boolean recordClap()
{
Log.d(TAG, "record clap");
boolean clapDetected = false;
try
{
recorder = AudioUtil.prepareRecorder(tmpAudioFile);
}
catch (IOException io)
{
Log.d(TAG, "failed to prepare recorder ", io);
throw new RecordingFailedException("failed to create recorder", io);
}
recorder.start();
int startAmplitude = recorder.getMaxAmplitude();
Log.d(TAG, "starting amplitude: " + startAmplitude);
do
{
Log.d(TAG, "waiting while recording...");
waitSome();
int finishAmplitude = recorder.getMaxAmplitude();
if (clipListener != null)
{
clipListener.heard(finishAmplitude);
}
int ampDifference = finishAmplitude - startAmplitude;
if (ampDifference >= amplitudeThreshold)
{
Log.d(TAG, "heard a clap!");
clapDetected = true;
}
Log.d(TAG, "finishing amplitude: " + finishAmplitude + " diff: "
+ ampDifference);
} while (continueRecording || !clapDetected);
Log.d(TAG, "stopped recording");
done();
return clapDetected;
}
private void waitSome()
{
try
{
// wait a while
Thread.sleep(clipTime);
} catch (InterruptedException e)
{
Log.d(TAG, "interrupted");
}
}
/**
* need to call this when completely done with recording
*/
public void done()
{
Log.d(TAG, "stop recording");
if (recorder != null)
{
if (isRecording())
{
stopRecording();
}
//now stop the media player
recorder.stop();
recorder.release();
}
}
public boolean isRecording()
{
return continueRecording;
}
public void stopRecording()
{
continueRecording = false;
}
}
您示例中的代码将对任何响亮的声音做出反应(不仅鼓掌)。它无法识别声音的性质。我对吗? – Elephant 2012-03-12 19:49:01
我意识到这是一个古老的,但我偶然发现它。我很确定,一般的开放域声音识别不是一个解决的问题。所以,不,你不会找到任何类型的库去做你想要的东西,因为这样的代码在任何地方都不存在。如果你挑选一些受限制的领域,你可以训练一个分类器来识别你感兴趣的各种声音,但这需要大量的数学,以及每个潜在声音的大量例子。如果你想要的图书馆存在,这将是非常酷的,但据我所知,这项技术还没有出现。
Musicg库对于哨子检测很有用。关于拍手,我不会推荐使用它,因为它会对每一个响亮的声音(甚至是演讲)作出反应。
对于拍手和其他敲击声音的检测,我推荐TarsosDSP。它有一个简单的API和丰富的功能(音高检测等)。对于拍手检测,你可以使用类似(如果你使用TarsosDSPAndroid-V3):
MicrophoneAudioDispatcher mDispatcher = new MicrophoneAudioDispatcher((int) SAMPLE_RATE, BUFFER_SIZE, BUFFER_OVERLAP);
double threshold = 8;
double sensitivity = 20;
mPercussionDetector = new PercussionOnsetDetector(22050, 1024,
new OnsetHandler() {
@Override
public void handleOnset(double time, double salience) {
Log.d(TAG, "Clap detected!");
}
}, sensitivity, threshold);
mDispatcher.addAudioProcessor(mPercussionDetector);
new Thread(mDispatcher).start();
您可以调整,通过调整灵敏度(0-100)和阈值(0-20)的探测器。
祝你好运!
看看这个帖子:http://stackoverflow.com/questions/2257075/real-time-audio-processing-in-android – coder 2011-12-15 17:53:47
是的,我读过关于AudioRecord类。该类的Read()方法返回原始数据,需要使用数学进行分析。但是我在问是否有第三方API可以在没有数学的情况下分析声音? – Elephant 2011-12-15 19:51:20