我正在寻找一个简单的解决方案,能够在C#中返回麦克风输入的整数值。我已经检查了网上可用的示例,但是没有一个在x64环境下工作(VS2008 + W7 x64)。
是否有任何简单的解决方案能够在C#中返回麦克风输入的振幅(或频率)值?
我尝试过NAudio,但没有结果。同时,这个http://www.codeproject.com/KB/audio-video/cswavrec.aspx?msg=2155497 也没有成功。
我正在寻找一个简单的解决方案,能够在C#中返回麦克风输入的整数值。我已经检查了网上可用的示例,但是没有一个在x64环境下工作(VS2008 + W7 x64)。
是否有任何简单的解决方案能够在C#中返回麦克风输入的振幅(或频率)值?
我尝试过NAudio,但没有结果。同时,这个http://www.codeproject.com/KB/audio-video/cswavrec.aspx?msg=2155497 也没有成功。
waveInOpen
函数获取输入设备。要确定使用哪个设备,你不需要枚举所有设备,而是可以查询每一个设备。调用waveInGetNumDevs
可返回安装设备的数量。然后,你可以针对每个设备调用waveInGetDevCaps
并检查这些属性。waveInAddBuffer
以获取小块数据。根据在waveInOpen
中指定的格式,字节表示原始音频数据。幅度为8位或16位有符号或无符号采样频率。 public void CaptureAudio()
{
using (var source = new SoundCardSource())
{
source.SampleRateKHz = 44.1;
source.SampleDataReady += this.OnSampleDataReady;
source.Start();
// Capture 5 seconds of audio...
Thread.Sleep(5000);
source.Stop();
}
}
private void OnSampleDataReady(object sender, SampleDataEventArgs e)
{
// Do something with e.Data short array on separate thread...
}
这里是SlimDX包装类的源代码:
using System;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;
using SlimDX.DirectSound;
using SlimDX.Multimedia;
public class SampleDataEventArgs : EventArgs
{
public SampleDataEventArgs(short[] data)
{
this.Data = data;
}
public short[] Data { get; private set; }
}
public class SoundCardSource : IDisposable
{
private volatile bool running;
private int bufferSize;
private CaptureBuffer buffer;
private CaptureBufferDescription bufferDescription;
private DirectSoundCapture captureDevice;
private WaveFormat waveFormat;
private Thread captureThread;
private List<NotificationPosition> notifications;
private int bufferPortionCount;
private int bufferPortionSize;
private WaitHandle[] waitHandles;
private double sampleRate;
public SoundCardSource()
{
this.waveFormat = new WaveFormat();
this.SampleRateKHz = 44.1;
this.bufferSize = 2048;
}
public event EventHandler<SampleDataEventArgs> SampleDataReady = delegate { };
public double SampleRateKHz
{
get
{
return this.sampleRate;
}
set
{
this.sampleRate = value;
if (this.running)
{
this.Restart();
}
}
}
public void Start()
{
if (this.running)
{
throw new InvalidOperationException();
}
if (this.captureDevice == null)
{
this.captureDevice = new DirectSoundCapture();
}
this.waveFormat.FormatTag = WaveFormatTag.Pcm; // Change to WaveFormatTag.IeeeFloat for float
this.waveFormat.BitsPerSample = 16; // Set this to 32 for float
this.waveFormat.BlockAlignment = (short)(waveFormat.BitsPerSample / 8);
this.waveFormat.Channels = 1;
this.waveFormat.SamplesPerSecond = (int)(this.SampleRateKHz * 1000D);
this.waveFormat.AverageBytesPerSecond =
this.waveFormat.SamplesPerSecond *
this.waveFormat.BlockAlignment *
this.waveFormat.Channels;
this.bufferPortionCount = 2;
this.bufferDescription.BufferBytes = this.bufferSize * sizeof(short) * bufferPortionCount;
this.bufferDescription.Format = this.waveFormat;
this.bufferDescription.WaveMapped = false;
this.buffer = new CaptureBuffer(this.captureDevice, this.bufferDescription);
this.bufferPortionSize = this.buffer.SizeInBytes / this.bufferPortionCount;
this.notifications = new List<NotificationPosition>();
for (int i = 0; i < this.bufferPortionCount; i++)
{
NotificationPosition notification = new NotificationPosition();
notification.Offset = this.bufferPortionCount - 1 + (bufferPortionSize * i);
notification.Event = new AutoResetEvent(false);
this.notifications.Add(notification);
}
this.buffer.SetNotificationPositions(this.notifications.ToArray());
this.waitHandles = new WaitHandle[this.notifications.Count];
for (int i = 0; i < this.notifications.Count; i++)
{
this.waitHandles[i] = this.notifications[i].Event;
}
this.captureThread = new Thread(new ThreadStart(this.CaptureThread));
this.captureThread.IsBackground = true;
this.running = true;
this.captureThread.Start();
}
public void Stop()
{
this.running = false;
if (this.captureThread != null)
{
this.captureThread.Join();
this.captureThread = null;
}
if (this.buffer != null)
{
this.buffer.Dispose();
this.buffer = null;
}
if (this.notifications != null)
{
for (int i = 0; i < this.notifications.Count; i++)
{
this.notifications[i].Event.Close();
}
this.notifications.Clear();
this.notifications = null;
}
}
public void Restart()
{
this.Stop();
this.Start();
}
private void CaptureThread()
{
int bufferPortionSamples = this.bufferPortionSize / sizeof(float);
// Buffer type must match this.waveFormat.FormatTag and this.waveFormat.BitsPerSample
short[] bufferPortion = new short[bufferPortionSamples];
int bufferPortionIndex;
this.buffer.Start(true);
while (this.running)
{
bufferPortionIndex = WaitHandle.WaitAny(this.waitHandles);
this.buffer.Read(
bufferPortion,
0,
bufferPortionSamples,
bufferPortionSize * Math.Abs((bufferPortionIndex - 1) % bufferPortionCount));
this.SampleDataReady(this, new SampleDataEventArgs(bufferPortion));
}
this.buffer.Stop();
}
public void Dispose()
{
this.Dispose(true);
GC.SuppressFinalize(this);
}
protected virtual void Dispose(bool disposing)
{
if (disposing)
{
this.Stop();
if (this.captureDevice != null)
{
this.captureDevice.Dispose();
this.captureDevice = null;
}
}
}
}
它是完全多线程的,以最小化延迟。我最初为实时信号处理分析工具编写了它,并使用浮点输出而不是短输出,但我修改了代码示例以匹配您请求的用法。如果您需要频率数据,我建议使用http://www.mathdotnet.com/Neodym.aspx或http://www.exocortex.org/dsp/作为一个很好的C# FFT库。