Unity 工具之 Azure 微软SSML语音合成TTS流式获取音频数据的简单整理

一、简单介绍

二、实现原理

三、实现步骤

四、关键代码

一、简单介绍

Unity 工具类，自己整理的一些游戏开发可能用到的模块，单独独立使用，方便游戏开发。

本节介绍，这里在使用微软的Azure 进行语音合成的两个方法的做简单整理，这里简单说明，如果你有更好的方法，欢迎留言交流。

语音合成标记语言 (SSML) 是一种基于 XML 的标记语言，可用于微调文本转语音输出属性，例如音调、发音、语速、音量等。与纯文本输入相比，你拥有更大的控制权和灵活性。

可以使用 SSML 来执行以下操作：

定义输入文本结构，用于确定文本转语音输出的结构、内容和其他特征。例如，可以使用 SSML 来定义段落、句子、中断/暂停或静音。可以使用事件标记（例如书签或视素）来包装文本，这些标记可以稍后由应用程序处理。
选择语音、语言、名称、样式和角色。可以在单个 SSML 文档中使用多个语音。调整重音、语速、音调和音量。还可以使用 SSML 插入预先录制的音频，例如音效或音符。
控制输出音频的发音。例如，可以将 SSML 与音素和自定义词典配合使用来改进发音。还可以使用 SSML 定义单词或数学表达式的具体发音。
下面是 SSML 文档的基本结构和语法的子集：
<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis" xmlns:mstts="https://www.w3.org/2001/mstts" xml:lang="string"><mstts:backgroundaudio src="string" volume="string" fadein="string" fadeout="string"/><voice name="string" effect="string"><audio src="string"></audio><bookmark mark="string"/><break strength="string" time="string" /><emphasis level="value"></emphasis><lang xml:lang="string"></lang><lexicon uri="string"/><math xmlns="http://www.w3.org/1998/Math/MathML"></math><mstts:audioduration value="string"/><mstts:express-as style="string" styledegree="value" role="string"></mstts:express-as><mstts:silence type="string" value="string"/><mstts:viseme type="string"/><p></p><phoneme alphabet="string" ph="string"></phoneme><prosody pitch="value" contour="value" range="value" rate="value" volume="value"></prosody><s></s><say-as interpret-as="string" format="string" detail="string"></say-as><sub alias="string"></sub></voice>
</speak>
SSML 语音和声音
语音合成标记语言 (SSML) 的语音和声音 - 语音服务 - Azure AI services | Microsoft Learn

官网注册：

面向学生的 Azure - 免费帐户额度 | Microsoft Azure

官网技术文档网址：

技术文档 | Microsoft Learn

官网的TTS：

文本转语音快速入门 - 语音服务 - Azure Cognitive Services | Microsoft Learn

Azure Unity SDK 包官网：

安装语音 SDK - Azure Cognitive Services | Microsoft Learn

SDK具体链接：

https://aka.ms/csspeech/unitypackage

二、实现原理

1、官网申请得到语音合成对应的 SPEECH_KEY 和 SPEECH_REGION

2、然后对应设置语言和需要的声音配置

3、使用 SSML 带有流式获取得到音频数据，在声源中播放或者保存即可，样例如下

public static async Task SynthesizeAudioAsync()
{var speechConfig = SpeechConfig.FromSubscription("YourSpeechKey", "YourSpeechRegion");using var speechSynthesizer = new SpeechSynthesizer(speechConfig, null);var ssml = File.ReadAllText("./ssml.xml");var result = await speechSynthesizer.SpeakSsmlAsync(ssml);using var stream = AudioDataStream.FromResult(result);await stream.SaveToWaveFileAsync("path/to/write/file.wav");
}

三、实现步骤

基础的环境搭建参照：Unity 工具之 Azure 微软语音合成普通方式和流式获取音频数据的简单整理_unity 语音合成

1、脚本实现，挂载对应脚本到场景中

2、运行场景，会使用 SSML方式合成TTS，并播放

四、关键代码

1、AzureTTSDataWithSSMLHandler

using Microsoft.CognitiveServices.Speech;
using System;
using System.Threading;
using System.Threading.Tasks;
using System.Xml;
using UnityEngine;/// <summary>
/// 使用 SSML 方式语音合成
/// </summary>
public class AzureTTSDataWithSSMLHandler
{/// <summary>/// Azure TTS 合成 必要数据/// </summary>private const string SPEECH_KEY = "YOUR_SPEECH_KEY";private const string SPEECH_REGION = "YOUR_SPEECH_REGION";private const string SPEECH_RECOGNITION_LANGUAGE = "zh-CN";private string SPEECH_VOICE_NAME = "zh-CN-XiaoxiaoNeural";/// <summary>/// 创建 TTS 中的参数/// </summary>private CancellationTokenSource m_CancellationTokenSource;private AudioDataStream m_AudioDataStream;private Connection m_Connection;private SpeechConfig m_Config;private SpeechSynthesizer m_Synthesizer;/// <summary>/// 音频获取事件/// </summary>private Action<AudioDataStream> m_AudioStream;/// <summary>/// 开始播放TTS事件/// </summary>private Action m_StartTTSPlayAction;/// <summary>/// 停止播放TTS事件/// </summary>private Action m_StartTTSStopAction;/// <summary>/// 初始化/// </summary>public void Initialized(){m_Config = SpeechConfig.FromSubscription(SPEECH_KEY, SPEECH_REGION);m_Synthesizer = new SpeechSynthesizer(m_Config, null);m_Connection = Connection.FromSpeechSynthesizer(m_Synthesizer);m_Connection.Open(true);}/// <summary>/// 开始进行语音合成/// </summary>/// <param name="msg">合成的内容</param>/// <param name="stream">获取到的音频流数据</param>/// <param name="style"></param>public async void Start(string msg, Action<AudioDataStream> stream, string style = "chat"){this.m_AudioStream = stream;await SynthesizeAudioAsync(CreateSSML(msg, SPEECH_RECOGNITION_LANGUAGE, SPEECH_VOICE_NAME, style));}/// <summary>/// 停止语音合成/// </summary>public void Stop(){m_StartTTSStopAction?.Invoke();if (m_AudioDataStream != null){m_AudioDataStream.Dispose();m_AudioDataStream = null;}if (m_CancellationTokenSource != null){m_CancellationTokenSource.Cancel();}if (m_Synthesizer != null){m_Synthesizer.Dispose();m_Synthesizer = null;}if (m_Connection != null){m_Connection.Dispose();m_Connection = null;}}/// <summary>/// 设置语音合成开始播放事件/// </summary>/// <param name="onStartAction"></param>public void SetStartTTSPlayAction(Action onStartAction){if (onStartAction != null){m_StartTTSPlayAction = onStartAction;}}/// <summary>/// 设置停止语音合成事件/// </summary>/// <param name="onAudioStopAction"></param>public void SetStartTTSStopAction(Action onAudioStopAction){if (onAudioStopAction != null){m_StartTTSStopAction = onAudioStopAction;}}/// <summary>/// 开始异步请求合成 TTS 数据/// </summary>/// <param name="speakMsg"></param>/// <returns></returns>private async Task SynthesizeAudioAsync(string speakMsg){Cancel();m_CancellationTokenSource = new CancellationTokenSource();var result = m_Synthesizer.StartSpeakingSsmlAsync(speakMsg);await result;m_StartTTSPlayAction?.Invoke();m_AudioDataStream = AudioDataStream.FromResult(result.Result);m_AudioStream?.Invoke(m_AudioDataStream);}private void Cancel(){if (m_AudioDataStream != null){m_AudioDataStream.Dispose();m_AudioDataStream = null;}if (m_CancellationTokenSource != null){m_CancellationTokenSource.Cancel();}}/// <summary>/// 生成 需要的 SSML XML 数据/// （格式不唯一，可以根据需要自行在增加删减）/// </summary>/// <param name="msg">合成的音频内容</param>/// <param name="language">合成语音</param>/// <param name="voiceName">采用谁的声音合成音频</param>/// <param name="style">合成时的语气类型</param>/// <returns>ssml XML</returns>private string CreateSSML(string msg, string language, string voiceName, string style = "chat"){// XmlDocumentXmlDocument xmlDoc = new XmlDocument();// 设置 speak 基础元素XmlElement speakElem = xmlDoc.CreateElement("speak");speakElem.SetAttribute("version", "1.0");speakElem.SetAttribute("xmlns", "http://www.w3.org/2001/10/synthesis");speakElem.SetAttribute("xmlns:mstts", "http://www.w3.org/2001/mstts");speakElem.SetAttribute("xml:lang", language);// 设置 voice 元素XmlElement voiceElem = xmlDoc.CreateElement("voice");voiceElem.SetAttribute("name", voiceName);// 设置 mstts:viseme 元素XmlElement visemeElem = xmlDoc.CreateElement("mstts", "viseme", "http://www.w3.org/2001/mstts");visemeElem.SetAttribute("type", "FacialExpression");// 设置 语气 元素XmlElement styleElem = xmlDoc.CreateElement("mstts", "express-as", "http://www.w3.org/2001/mstts");styleElem.SetAttribute("style", style.ToString().Replace("_", "-"));// 创建文本节点，包含文本信息XmlNode textNode = xmlDoc.CreateTextNode(msg);// 设置好的元素添加到 xml 中voiceElem.AppendChild(visemeElem);styleElem.AppendChild(textNode);voiceElem.AppendChild(styleElem);speakElem.AppendChild(voiceElem);xmlDoc.AppendChild(speakElem);Debug.Log("[SSML  XML] Result : " + xmlDoc.OuterXml);return xmlDoc.OuterXml;}}

2、AzureTTSMono

using Microsoft.CognitiveServices.Speech;
using System;
using System.Collections.Concurrent;
using System.IO;
using UnityEngine;[RequireComponent(typeof(AudioSource))]
public class AzureTTSMono : MonoBehaviour
{private AzureTTSDataWithSSMLHandler m_AzureTTSDataWithSSMLHandler;/// <summary>/// 音源和音频参数/// </summary>private AudioSource m_AudioSource;private AudioClip m_AudioClip;/// <summary>/// 音频流数据/// </summary>private ConcurrentQueue<float[]> m_AudioDataQueue = new ConcurrentQueue<float[]>();private AudioDataStream m_AudioDataStream;/// <summary>/// 音频播放完的事件/// </summary>private Action m_AudioEndAction;/// <summary>/// 音频播放结束的布尔变量/// </summary>private bool m_NeedPlay = false;private bool m_StreamReadEnd = false;private const int m_SampleRate = 16000;//最大支持60s音频 private const int m_BufferSize = m_SampleRate * 60;//采样容量private const int m_UpdateSize = m_SampleRate;//audioclip 设置过的数据个数private int m_TotalCount = 0;private int m_DataIndex = 0;#region Lifecycle functionprivate void Awake(){m_AudioSource = GetComponent<AudioSource>();m_AzureTTSDataWithSSMLHandler = new AzureTTSDataWithSSMLHandler();m_AzureTTSDataWithSSMLHandler.SetStartTTSPlayAction(() => { Debug.Log(" Play TTS "); });m_AzureTTSDataWithSSMLHandler.SetStartTTSStopAction(() => { Debug.Log(" Stop TTS "); AudioPlayEndEvent(); });m_AudioEndAction = () => { Debug.Log(" End TTS "); };m_AzureTTSDataWithSSMLHandler.Initialized();}// Start is called before the first frame updatevoid Start(){m_AzureTTSDataWithSSMLHandler.Start("今朝有酒，今朝醉，人生几年百花春", OnGetAudioStream);}// Update is called once per frameprivate void Update(){UpdateAudio();}#endregion#region Audio handler/// <summary>/// 设置播放TTS的结束的结束事件/// </summary>/// <param name="act"></param>public void SetAudioEndAction(Action act){this.m_AudioEndAction = act;}/// <summary>/// 处理获取到的TTS流式数据/// </summary>/// <param name="stream">流数据</param>public async void OnGetAudioStream(AudioDataStream stream){m_StreamReadEnd = false;m_NeedPlay = true;m_AudioDataStream = stream;Debug.Log("[AzureTTSMono] OnGetAudioStream");MemoryStream memStream = new MemoryStream();byte[] buffer = new byte[m_UpdateSize * 2];uint bytesRead;m_DataIndex = 0;m_TotalCount = 0;m_AudioDataQueue.Clear();// 回到主线程进行数据处理Loom.QueueOnMainThread(() =>{m_AudioSource.Stop();m_AudioSource.clip = null;m_AudioClip = AudioClip.Create("SynthesizedAudio", m_BufferSize, 1, m_SampleRate, false);m_AudioSource.clip = m_AudioClip;});do{bytesRead = await System.Threading.Tasks.Task.Run(() => m_AudioDataStream.ReadData(buffer));if (bytesRead <= 0){break;}// 读取写入数据memStream.Write(buffer, 0, (int)bytesRead);{var tempData = memStream.ToArray();var audioData = new float[memStream.Length / 2];for (int i = 0; i < audioData.Length; ++i){audioData[i] = (short)(tempData[i * 2 + 1] << 8 | tempData[i * 2]) / 32768.0F;}try{m_TotalCount += audioData.Length;// 把数据添加到队列中m_AudioDataQueue.Enqueue(audioData);// new 获取新的地址，为后面写入数据memStream = new MemoryStream();}catch (Exception e){Debug.LogError(e.ToString());}}} while (bytesRead > 0);m_StreamReadEnd = true;}/// <summary>/// Update 播放音频/// </summary>private void UpdateAudio() {if (!m_NeedPlay) return;//数据操作if (m_AudioDataQueue.TryDequeue(out float[] audioData)){m_AudioClip.SetData(audioData, m_DataIndex);m_DataIndex = (m_DataIndex + audioData.Length) % m_BufferSize;}//检测是否停止if (m_StreamReadEnd && m_AudioSource.timeSamples >= m_TotalCount){AudioPlayEndEvent();}if (!m_NeedPlay) return;//由于网络，可能额有些数据还没有过来，所以根据需要判断是否暂停播放if (m_AudioSource.timeSamples >= m_DataIndex && m_AudioSource.isPlaying){m_AudioSource.timeSamples = m_DataIndex;//暂停Debug.Log("[AzureTTSMono] Pause");m_AudioSource.Pause();}//由于网络，可能有些数据过来比较晚，所以这里根据需要判断是否继续播放if (m_AudioSource.timeSamples < m_DataIndex && !m_AudioSource.isPlaying){//播放Debug.Log("[AzureTTSMono] Play");m_AudioSource.Play();}}/// <summary>/// TTS 播放结束的事件/// </summary>private void AudioPlayEndEvent(){Debug.Log("[AzureTTSMono] End");m_NeedPlay = false;m_AudioSource.timeSamples = 0;m_AudioSource.Stop();m_AudioEndAction?.Invoke();}#endregion
}