基于Accord.Audio和百度语言识别

时间:2021-10-28 09:17:14

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我的各种github 开源项目和代码:https://github.com/linbin524

目标需求

使用录音形式,模拟微信语音聊天。按住录音,松开发送语音,并完成语音识别。

ps:百度的语言识别有60秒长度限制,需要自己做好控制。

实现方案

采用C# winform 程序实现桌面版,采用Accord 实现语音录制停止等基础语音操作,操作停止按钮,

自动调用百度语言识别接口将识别内容显示在文本框中。

备注,语音识别需要配套阵列麦克风,(请先注册百度开发者)百度语音识别接口请参考:http://ai.baidu.com/docs#/ASR-Online-Csharp-SDK/top

 

实现效果展示

基于Accord.Audio和百度语言识别

实现过程

1、下载Accord 完成语音操作引用

accord 官方 地址:http://accord-framework.net/intro.html

官网中有示例demo,笔者的就是在示例demo上做改造的。

基于Accord.Audio和百度语言识别

建立自己的项目,引用包中的dll

基于Accord.Audio和百度语言识别

界面代码:

using System;
using System.Drawing;
using System.IO;
using System.Windows.Forms;
using Accord.Audio;
using Accord.Audio.Formats;
using Accord.DirectSound;
using Accord.Audio.Filters;
using Baidu.Aip.API; namespace SampleApp
{ public partial class MainForm : Form
{
private MemoryStream stream; private IAudioSource source;
private IAudioOutput output; private WaveEncoder encoder;
private WaveDecoder decoder; private float[] current; private int frames;
private int samples;
private TimeSpan duration;
/// <summary>
/// 备注,语音识别需要配套阵列麦克风
/// </summary> public MainForm()
{
InitializeComponent(); // Configure the wavechart
chart.SimpleMode = true;
chart.AddWaveform("wave", Color.Green, , false); updateButtons();
// Application.Idle += ProcessFrame;
} void ProcessFrame(object sender, EventArgs e) { }
/// <summary>
/// 从声卡开始录制音频
/// </summary>
///
private void btnRecord_Click(object sender, EventArgs e)
{
// Create capture device
source = new AudioCaptureDevice()//这里是核心
{
// Listen on 22050 Hz
DesiredFrameSize = ,
SampleRate = ,//采样率
//SampleRate = 22050,//采样率
Channels=,
// We will be reading 16-bit PCM
Format = SampleFormat.Format16Bit
}; // Wire up some events
source.NewFrame += source_NewFrame;
source.AudioSourceError += source_AudioSourceError; // Create buffer for wavechart control
current = new float[source.DesiredFrameSize]; // Create stream to store file
stream = new MemoryStream();
encoder = new WaveEncoder(stream); // Start
source.Start();
updateButtons();
} /// <summary>
/// 播放录制的音频流。
/// </summary>
///
private void btnPlay_Click(object sender, EventArgs e)
{
// First, we rewind the stream
stream.Seek(, SeekOrigin.Begin); // Then we create a decoder for it
decoder = new WaveDecoder(stream); // Configure the track bar so the cursor
// can show the proper current position
if (trackBar1.Value < decoder.Frames)
decoder.Seek(trackBar1.Value);
trackBar1.Maximum = decoder.Samples; // Here we can create the output audio device that will be playing the recording
output = new AudioOutputDevice(this.Handle, decoder.SampleRate, decoder.Channels); // Wire up some events
output.FramePlayingStarted += output_FramePlayingStarted;
output.NewFrameRequested += output_NewFrameRequested;
output.Stopped += output_PlayingFinished; // Start playing!
output.Play(); updateButtons();
} /// <summary>
/// 停止录制或播放流。
/// </summary>
///
private void btnStop_Click(object sender, EventArgs e)
{
// Stops both cases
if (source != null)
{
// If we were recording
source.SignalToStop();
source.WaitForStop();
}
if (output != null)
{
// If we were playing
output.SignalToStop();
output.WaitForStop();
} updateButtons(); // Also zero out the buffers and screen
Array.Clear(current, , current.Length);
updateWaveform(current, current.Length);
SpeechAPI speechApi = new SpeechAPI(); string result = speechApi.AsrData(stream,"wav");
tb_result.Text = "语音识别结果:"+result;
} /// <summary>
/// 当音频有错误时,将调用这个回调函数。
///
///
/// </summary>
///
private void source_AudioSourceError(object sender, AudioSourceErrorEventArgs e)
{
throw new Exception(e.Description);
} /// <summary>
///
/// 每当有新的输入音频帧时,该方法将被调用。
///
/// </summary>
///
private void source_NewFrame(object sender, NewFrameEventArgs eventArgs)
{ eventArgs.Signal.CopyTo(current); updateWaveform(current, eventArgs.Signal.Length); encoder.Encode(eventArgs.Signal); duration += eventArgs.Signal.Duration; samples += eventArgs.Signal.Samples;
frames += eventArgs.Signal.Length;
} private void output_FramePlayingStarted(object sender, PlayFrameEventArgs e)
{
updateTrackbar(e.FrameIndex); if (e.FrameIndex + e.Count < decoder.Frames)
{
int previous = decoder.Position;
decoder.Seek(e.FrameIndex); Signal s = decoder.Decode(e.Count);
decoder.Seek(previous); updateWaveform(s.ToFloat(), s.Length);
}
} private void output_PlayingFinished(object sender, EventArgs e)
{
updateButtons(); Array.Clear(current, , current.Length);
updateWaveform(current, current.Length);
} ///
private void output_NewFrameRequested(object sender, NewFrameRequestedEventArgs e)
{ e.FrameIndex = decoder.Position; Signal signal = decoder.Decode(e.Frames); if (signal == null)
{ e.Stop = true;
return;
} e.Frames = signal.Length; signal.CopyTo(e.Buffer);
} private void updateWaveform(float[] samples, int length)
{
if (InvokeRequired)
{
BeginInvoke(new Action(() =>
{
chart.UpdateWaveform("wave", samples, length);
}));
}
else
{
chart.UpdateWaveform("wave", current, length);
}
} ///
private void updateTrackbar(int value)
{
if (InvokeRequired)
{
BeginInvoke(new Action(() =>
{
trackBar1.Value = Math.Max(trackBar1.Minimum, Math.Min(trackBar1.Maximum, value));
}));
}
else
{
trackBar1.Value = Math.Max(trackBar1.Minimum, Math.Min(trackBar1.Maximum, value));
}
} private void updateButtons()
{
if (InvokeRequired)
{
BeginInvoke(new Action(updateButtons));
return;
} if (source != null && source.IsRunning)
{
btnBwd.Enabled = false;
btnFwd.Enabled = false;
btnPlay.Enabled = false;
btnStop.Enabled = true;
btnRecord.Enabled = false;
trackBar1.Enabled = false;
}
else if (output != null && output.IsRunning)
{
btnBwd.Enabled = false;
btnFwd.Enabled = false;
btnPlay.Enabled = false;
btnStop.Enabled = true;
btnRecord.Enabled = false;
trackBar1.Enabled = true;
}
else
{
btnBwd.Enabled = false;
btnFwd.Enabled = false;
btnPlay.Enabled = stream != null;
btnStop.Enabled = false;
btnRecord.Enabled = true;
trackBar1.Enabled = decoder != null; trackBar1.Value = ;
}
} private void MainFormFormClosed(object sender, FormClosedEventArgs e)
{
if (source != null) source.SignalToStop();
if (output != null) output.SignalToStop();
} private void saveFileDialog1_FileOk(object sender, System.ComponentModel.CancelEventArgs e)
{
Stream fileStream = saveFileDialog1.OpenFile();
stream.WriteTo(fileStream);
fileStream.Close();
} private void saveToolStripMenuItem_Click(object sender, EventArgs e)
{
saveFileDialog1.ShowDialog(this);
} private void updateTimer_Tick(object sender, EventArgs e)
{
lbLength.Text = String.Format("Length: {0:00.00} sec.", duration.Seconds); } private void aboutToolStripMenuItem_Click(object sender, EventArgs e)
{
new AboutBox().ShowDialog(this);
} private void closeToolStripMenuItem_Click(object sender, EventArgs e)
{
Close();
} private void btnIncreaseVolume_Click(object sender, EventArgs e)
{
adjustVolume(1.25f);
} private void btnDecreaseVolume_Click(object sender, EventArgs e)
{
adjustVolume(0.75f);
} private void adjustVolume(float value)
{ stream.Seek(, SeekOrigin.Begin); decoder = new WaveDecoder(stream); var signal = decoder.Decode(); var volume = new VolumeFilter(value);
volume.ApplyInPlace(signal); stream.Seek(, SeekOrigin.Begin);
encoder = new WaveEncoder(stream);
encoder.Encode(signal);
} }
}

 百度语音识别接口

百度已经提供sdk,对于支持语音格式如下。

支持的语音格式

原始 PCM 的录音参数必须符合 8k/16k 采样率、16bit 位深、单声道,支持的格式有:pcm(不压缩)、wav(不压缩,pcm编码)、amr(压缩格式)。

        public string AsrData(string filePath, string format = "pcm", int rate = )
{
var data =File.ReadAllBytes(filePath);
var result = _asrClient.Recognize(data, format, );
return result.ToString();
}

 结果评测:

对于普通的语言识别效果不好,需要阵列麦克风才可以。

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