本文主要是介绍UnityWebGL使用sherpa-ncnn实时语音识别,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!
k2-fsa/sherpa-ncnn:在没有互联网连接的情况下使用带有 ncnn 的下一代 Kaldi 进行实时语音识别。支持iOS、Android、Raspberry Pi、VisionFive2、LicheePi4A等。 (github.com)
如果是PC端可以直接使用ssssssilver大佬的 https://github.com/ssssssilver/sherpa-ncnn-unity.git
我这边要折腾的是WebGL版本的,所以修改了一番
1、WebSocket,客户端使用了psygames/UnityWebSocket: :whale: The Best Unity WebSocket Plugin for All Platforms. (github.com)
using System;
using System.Collections.Generic;
using System.Runtime.InteropServices;
using System.Text;
using UnityEngine;
using UnityEngine.UI;
using UnityWebSocket;public class uSherpaWebGL : MonoBehaviour
{IWebSocket ws;public Text text;Queue<string> msgs = new Queue<string>();// Start is called before the first frame updatevoid Start(){ws = new WebSocket("ws://127.0.0.1:9999");ws.OnOpen += OnOpen;ws.OnMessage += OnMessage;ws.OnError += OnError;ws.OnClose += OnClose;ws.ConnectAsync();}// Update is called once per framevoid Update(){if (msgs.Count > 0){string msg = msgs.Dequeue();text.text += msg;}}byte[] desArray;public void OnData(float[] input){Debug.Log("input.Length:" + input.Length);SendData(input);}void SendData(float[] input){var desArraySize = Buffer.ByteLength(input);IntPtr srcArrayPtr = Marshal.UnsafeAddrOfPinnedArrayElement(input, 0);desArray = new byte[desArraySize];Marshal.Copy(srcArrayPtr, desArray, 0, desArraySize);if (ws != null && ws.ReadyState == WebSocketState.Open){ws.SendAsync(desArray);}}void OnOpen(object sender, OpenEventArgs e){Debug.Log("WS connected!");}void OnMessage(object sender, MessageEventArgs e){if (e.IsBinary){string str = Encoding.UTF8.GetString(e.RawData);Debug.Log("WS received message: " + str);msgs.Enqueue(str);}else if (e.IsText){}}void OnError(object sender, ErrorEventArgs e){Debug.Log("WS error: " + e.Message);}void OnClose(object sender, CloseEventArgs e){Debug.Log(string.Format("Closed: StatusCode: {0}, Reason: {1}", e.StatusCode, e.Reason));}private void OnApplicationQuit(){if (ws != null && ws.ReadyState != WebSocketState.Closed){ws.CloseAsync();}}
}
服务器端使用了Fleck
// See https://aka.ms/new-console-template for more information
using Fleck;
using System.Text;namespace uSherpaServer
{internal class Program{// 声明配置和识别器变量static SherpaNcnn.OnlineRecognizer recognizer;static SherpaNcnn.OnlineStream onlineStream;static string tokensPath = "tokens.txt";static string encoderParamPath = "encoder_jit_trace-pnnx.ncnn.param";static string encoderBinPath = "encoder_jit_trace-pnnx.ncnn.bin";static string decoderParamPath = "decoder_jit_trace-pnnx.ncnn.param";static string decoderBinPath = "decoder_jit_trace-pnnx.ncnn.bin";static string joinerParamPath = "joiner_jit_trace-pnnx.ncnn.param";static string joinerBinPath = "joiner_jit_trace-pnnx.ncnn.bin";static int numThreads = 1;static string decodingMethod = "greedy_search";static string modelPath;static float sampleRate = 16000;static IWebSocketConnection client;static void Main(string[] args){//需要将此文件夹拷贝到exe所在的目录modelPath = Environment.CurrentDirectory + "/sherpa-ncnn-streaming-zipformer-small-bilingual-zh-en-2023-02-16";// 初始化配置SherpaNcnn.OnlineRecognizerConfig config = new SherpaNcnn.OnlineRecognizerConfig{FeatConfig = { SampleRate = sampleRate, FeatureDim = 80 },ModelConfig = {Tokens = Path.Combine(modelPath,tokensPath),EncoderParam = Path.Combine(modelPath,encoderParamPath),EncoderBin =Path.Combine(modelPath, encoderBinPath),DecoderParam =Path.Combine(modelPath, decoderParamPath),DecoderBin = Path.Combine(modelPath, decoderBinPath),JoinerParam = Path.Combine(modelPath,joinerParamPath),JoinerBin =Path.Combine(modelPath,joinerBinPath),UseVulkanCompute = 0,NumThreads = numThreads},DecoderConfig = {DecodingMethod = decodingMethod,NumActivePaths = 4},EnableEndpoint = 1,Rule1MinTrailingSilence = 2.4F,Rule2MinTrailingSilence = 1.2F,Rule3MinUtteranceLength = 20.0F};// 创建识别器和在线流recognizer = new SherpaNcnn.OnlineRecognizer(config);onlineStream = recognizer.CreateStream();StartWebServer();Update();Console.ReadLine();}static void StartWebServer(){//存储连接对象的池var connectSocketPool = new List<IWebSocketConnection>();//创建WebSocket服务端实例并监听本机的9999端口var server = new WebSocketServer("ws://127.0.0.1:9999");//开启监听server.Start(socket =>{//注册客户端连接建立事件socket.OnOpen = () =>{client = socket;Console.WriteLine("Open");//将当前客户端连接对象放入连接池中connectSocketPool.Add(socket);};//注册客户端连接关闭事件socket.OnClose = () =>{client = null;Console.WriteLine("Close");//将当前客户端连接对象从连接池中移除connectSocketPool.Remove(socket);};//注册客户端发送信息事件socket.OnBinary = message =>{float[] floatArray = new float[message.Length / 4];Buffer.BlockCopy(message, 0, floatArray, 0, message.Length);// 将采集到的音频数据传递给识别器onlineStream.AcceptWaveform(sampleRate, floatArray);};});}static string lastText = "";static void Update(){while (true){// 每帧更新识别器状态if (recognizer.IsReady(onlineStream)){recognizer.Decode(onlineStream);}var text = recognizer.GetResult(onlineStream).Text;bool isEndpoint = recognizer.IsEndpoint(onlineStream);if (!string.IsNullOrWhiteSpace(text) && lastText != text){if (string.IsNullOrWhiteSpace(lastText)){lastText = text;if (client != null){client.Send(Encoding.UTF8.GetBytes(text));//Console.WriteLine("text1:" + text);}}else{if (client != null){client.Send(Encoding.UTF8.GetBytes(text.Replace(lastText, "")));lastText = text;}}}if (isEndpoint){if (!string.IsNullOrWhiteSpace(text)){if (client != null){client.Send(Encoding.UTF8.GetBytes("。"));}// Console.WriteLine("text2:" + text);}recognizer.Reset(onlineStream);//Console.WriteLine("Reset");}Thread.Sleep(200); // ms}}}
}
2、Unity录音插件使用了uMicrophoneWebGL 绑定DataEvent事件实时获取话筒数据(float数组)
最后放上工程地址
客户端 uSherpa: fork from https://github.com/ssssssilver/sherpa-ncnn-unity.git改成 Unity WebGL版
服务器端 GitHub - xue-fei/uSherpaServer: uSherpaServer 给Unity提供流式语音识别的websocket服务
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