\u76f8\u6bd4Tacotron+WaveNet\u6216FastSpeech\u7cfb\u5217，Sambert-Hifigan \u5728\u4ee5\u4e0b\u65b9\u9762\u5177\u6709\u663e\u8457\u4f18\u52bf：<\/p>\n
| \u7279\u6027 | \u8bf4\u660e |
\n|——|——|
\n| \u97f3\u8d28\u8868\u73b0 | \u652f\u630124kHz\u91c7\u6837\u7387\u8f93\u51fa，\u8bed\u97f3\u81ea\u7136\u6d41\u7545，\u63a5\u8fd1\u771f\u4eba\u53d1\u97f3 |
\n| \u60c5\u611f\u8868\u8fbe | \u5185\u7f6e\u591a\u60c5\u611f\u5efa\u6a21\u80fd\u529b，\u53ef\u751f\u6210\u559c\u60a6\u3001\u60b2\u4f24\u3001\u6124\u6012\u7b49\u591a\u79cd\u60c5\u7eea\u8bed\u8c03 |
\n| \u63a8\u7406\u6548\u7387 | \u58f0\u7801\u5668Hifi-GAN\u7ed3\u6784\u7b80\u6d01，\u9002\u5408CPU\u63a8\u7406，\u5ef6\u8fdf\u53ef\u63a7 |
\n| \u4e2d\u6587\u4f18\u5316 | \u8bad\u7ec3\u6570\u636e\u4ee5\u4e2d\u6587\u4e3a\u4e3b，\u5bf9\u62fc\u97f3\u3001\u58f0\u8c03\u3001\u8bed\u6c14\u8bcd\u5904\u7406\u66f4\u7cbe\u51c6 |<\/p>\n
\u66f4\u91cd\u8981\u7684\u662f，\u8be5\u6a21\u578b\u5df2\u901a\u8fc7ModelScope\u5e73\u53f0\u5f00\u6e90，\u63d0\u4f9b\u5b8c\u6574\u9884\u8bad\u7ec3\u6743\u91cd\u548c\u63a8\u7406\u811a\u672c，\u6781\u5927\u964d\u4f4e\u4e86\u4f7f\u7528\u95e8\u69db\u3002<\/p>\n
📌 \u5173\u952e\u6d1e\u5bdf：
\n\u7ecf\u5b9e\u6d4b，\u57284\u6838CPU（\u5982Intel Xeon E5-2680v4）\u73af\u5883\u4e0b，\u4e00\u6bb5150\u5b57\u7684\u4e2d\u6587\u6587\u672c\u5408\u6210\u65f6\u95f4\u7ea6\u4e3a3~5\u79d2，\u5185\u5b58\u5360\u7528\u4f4e\u4e8e2GB，\u5b8c\u5168\u6ee1\u8db3\u4e2d\u5c0f\u6d41\u91cf\u573a\u666f\u7684\u5b9e\u65f6\u54cd\u5e94\u9700\u6c42\u3002<\/p>\n
\n
\u7cfb\u7edf\u67b6\u6784\u8bbe\u8ba1：WebUI + API \u53cc\u6a21\u670d\u52a1<\/h3>\n
\u4e3a\u4e86\u517c\u987e\u6613\u7528\u6027\u4e0e\u6269\u5c55\u6027，\u6211\u4eec\u91c7\u7528\u5982\u4e0b\u7cfb\u7edf\u67b6\u6784：<\/p>\n
+——————+ +———————+
\n| \u7528\u6237\u6d4f\u89c8\u5668 | \u2194\u2192 | Flask HTTP Server |
\n+——————+ +———-+———-+
\n \u2193
\n +—————-+——————+
\n | Sambert-Hifigan Inference Engine |
\n +—————-+——————+
\n \u2193
\n Audio File (.wav)<\/p>\n
\u6838\u5fc3\u7ec4\u4ef6\u8bf4\u660e<\/h4>\n
\u524d\u7aef\u4ea4\u4e92\u5c42（WebUI）
\n \u63d0\u4f9b\u76f4\u89c2\u7684HTML\u9875\u9762，\u7528\u6237\u8f93\u5165\u6587\u672c\u540e\u70b9\u51fb\u6309\u94ae\u89e6\u53d1\u5408\u6210\u8bf7\u6c42，\u7ed3\u679c\u4ee5\u97f3\u9891\u63a7\u4ef6\u5f62\u5f0f\u8fd4\u56de，\u652f\u6301\u5728\u7ebf\u64ad\u653e\u4e0e\u4e0b\u8f7d\u3002<\/p>\n<\/li>\n
\u670d\u52a1\u63a5\u53e3\u5c42（Flask）
\n \u8d1f\u8d23\u63a5\u6536HTTP\u8bf7\u6c42\u3001\u53c2\u6570\u6821\u9a8c\u3001\u8c03\u7528\u6a21\u578b\u63a8\u7406\u3001\u8fd4\u56de\u97f3\u9891\u6587\u4ef6\u6216URL\u94fe\u63a5\u3002\u540c\u65f6\u652f\u6301GET\/POST\u63a5\u53e3，\u4fbf\u4e8e\u7b2c\u4e09\u65b9\u7cfb\u7edf\u96c6\u6210\u3002<\/p>\n<\/li>\n
\u6a21\u578b\u63a8\u7406\u5f15\u64ce
\n \u52a0\u8f7dSambert\u4e0eHifi-GAN\u6a21\u578b，\u6267\u884c\u5b8c\u6574\u7684\u6587\u672c\u2192\u9891\u8c31\u2192\u6ce2\u5f62\u6d41\u7a0b\u3002\u6240\u6709\u4f9d\u8d56\u5e93\u5df2\u5b8c\u6210\u7248\u672c\u9501\u5b9a，\u907f\u514d\u8fd0\u884c\u65f6\u51b2\u7a81\u3002<\/p>\n<\/li>\n
\u8d44\u6e90\u7ba1\u7406\u673a\u5236
\n \u81ea\u52a8\u6e05\u7406\u8fc7\u671f\u97f3\u9891\u6587\u4ef6（\u4fdd\u7559\u6700\u8fd110\u4e2a），\u9632\u6b62\u78c1\u76d8\u7a7a\u95f4\u8017\u5c3d；\u652f\u6301\u5e76\u53d1\u8bf7\u6c42\u961f\u5217\u63a7\u5236，\u4fdd\u969c\u670d\u52a1\u7a33\u5b9a\u6027\u3002<\/p>\n<\/li>\n
\n
\u5b9e\u8df5\u90e8\u7f72：\u4ece\u955c\u50cf\u542f\u52a8\u5230\u670d\u52a1\u4e0a\u7ebf<\/h3>\n
\u672c\u9879\u76ee\u5df2\u6253\u5305\u4e3aDocker\u955c\u50cf，\u5185\u7f6e\u5168\u90e8\u4f9d\u8d56\u73af\u5883，\u771f\u6b63\u505a\u5230\u201c\u4e00\u952e\u90e8\u7f72\u201d\u3002<\/p>\n
\u2705 \u90e8\u7f72\u6b65\u9aa4\u8be6\u89e3<\/h4>\n1. \u542f\u52a8\u5bb9\u5668\u670d\u52a1<\/h5>\n
docker run -p 5000:5000 your-image-name:sambert-hifigan-chinese<\/p>\n
\u5bb9\u5668\u542f\u52a8\u540e，Flask\u670d\u52a1\u9ed8\u8ba4\u76d1\u542c 5000 \u7aef\u53e3\u3002<\/p>\n
2. \u8bbf\u95eeWeb\u754c\u9762<\/h5>\n
\u5728\u6d4f\u89c8\u5668\u4e2d\u6253\u5f00\u5e73\u53f0\u63d0\u4f9b\u7684HTTP\u8bbf\u95ee\u5730\u5740（\u901a\u5e38\u4e3a http:\/\/<server-ip>:5000），\u5373\u53ef\u770b\u5230\u5982\u4e0b\u754c\u9762：<\/p>\n
![\"WebUI\u754c\u9762\u793a\u610f\u56fe\"](\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260114064134-69673a9e73235.png\")
<\/p>\n
💡 \u4f7f\u7528\u63d0\u793a：
\n– \u8f93\u5165\u6846\u652f\u6301\u957f\u6587\u672c（\u5efa\u8bae\u4e0d\u8d85\u8fc7500\u5b57\u7b26）
\n– \u70b9\u51fb\u201c\u5f00\u59cb\u5408\u6210\u8bed\u97f3\u201d\u540e，\u9875\u9762\u4f1a\u663e\u793a\u52a0\u8f7d\u52a8\u753b，\u5b8c\u6210\u540e\u81ea\u52a8\u64ad\u653e\u97f3\u9891
\n– \u97f3\u9891\u6587\u4ef6\u4ee5 .wav \u683c\u5f0f\u4fdd\u5b58\u4e8e \/app\/static\/audio\/ \u76ee\u5f55，\u53ef\u901a\u8fc7 \/static\/audio\/xxx.wav \u76f4\u63a5\u8bbf\u95ee<\/p>\n
3. \u8c03\u7528API\u63a5\u53e3（\u9002\u7528\u4e8e\u7a0b\u5e8f\u96c6\u6210）<\/h5>\n
\u9664\u4e86\u56fe\u5f62\u754c\u9762，\u7cfb\u7edf\u8fd8\u66b4\u9732\u6807\u51c6RESTful API，\u4fbf\u4e8e\u81ea\u52a8\u5316\u8c03\u7528\u3002<\/p>\n
🔧 API\u7aef\u70b9：\/api\/tts<\/h6>\n
\u8bf7\u6c42\u65b9\u5f0f：POST
\nContent-Type：application\/json<\/p>\n
\u8bf7\u6c42\u4f53\u793a\u4f8b：<\/p>\n
{
\n "text": "\u4eca\u5929\u5929\u6c14\u771f\u597d，\u6211\u4eec\u4e00\u8d77\u53bb\u516c\u56ed\u6563\u6b65\u5427！",
\n "emotion": "happy"
\n}<\/p>\n
\u54cd\u5e94\u683c\u5f0f：<\/p>\n
{
\n "status": "success",
\n "audio_url": "\/static\/audio\/output_20250405_120012.wav",
\n "duration": 3.2
\n}<\/p>\n
Python\u8c03\u7528\u793a\u4f8b：<\/p>\n
import requests<\/p>\n
url = "http:\/\/localhost:5000\/api\/tts"
\ndata = {
\n "text": "\u6b22\u8fce\u4f7f\u7528Sambert-Hifigan\u8bed\u97f3\u5408\u6210\u670d\u52a1",
\n "emotion": "neutral"
\n}<\/p>\n
response = requests.post(url, json=data)
\nresult = response.json()<\/p>\n
if result["status"] == "success":
\n print("\u97f3\u9891\u751f\u6210\u6210\u529f，\u4e0b\u8f7d\u5730\u5740：", result["audio_url"])
\n # \u53ef\u8fdb\u4e00\u6b65\u4f7f\u7528requests.get(result["audio_url"]) \u4e0b\u8f7d\u6587\u4ef6
\nelse:
\n print("\u5408\u6210\u5931\u8d25：", result["message"])<\/p>\n
\n
\u6838\u5fc3\u4ee3\u7801\u89e3\u6790：Flask\u670d\u52a1\u4e0e\u6a21\u578b\u96c6\u6210<\/h3>\n
\u4ee5\u4e0b\u662f\u5173\u952e\u6a21\u5757\u7684\u5b9e\u73b0\u4ee3\u7801，\u5c55\u793a\u4e86\u5982\u4f55\u5c06Sambert-Hifigan\u6a21\u578b\u5d4c\u5165Web\u670d\u52a1\u3002<\/p>\n
📁 \u9879\u76ee\u76ee\u5f55\u7ed3\u6784<\/h4>\n
\/app
\n\u251c\u2500\u2500 app.py # Flask\u4e3b\u7a0b\u5e8f
\n\u251c\u2500\u2500 models\/
\n\u2502 \u251c\u2500\u2500 sambert_model.bin # \u9884\u8bad\u7ec3\u58f0\u5b66\u6a21\u578b
\n\u2502 \u2514\u2500\u2500 hifigan_model.bin # \u58f0\u7801\u5668\u6a21\u578b
\n\u251c\u2500\u2500 static\/
\n\u2502 \u2514\u2500\u2500 audio\/ # \u5b58\u653e\u751f\u6210\u7684wav\u6587\u4ef6
\n\u251c\u2500\u2500 templates\/
\n\u2502 \u2514\u2500\u2500 index.html # Web\u524d\u7aef\u9875\u9762
\n\u2514\u2500\u2500 tts_engine.py # \u6a21\u578b\u52a0\u8f7d\u4e0e\u63a8\u7406\u5c01\u88c5<\/p>\n
🧠 \u6a21\u578b\u63a8\u7406\u5c01\u88c5（tts_engine.py）<\/h4>\n
# tts_engine.py
\nfrom modelscope.pipelines import pipeline
\nfrom modelscope.utils.constant import Tasks<\/p>\n
class TTSProcessor:
\n def __init__(self):
\n self.tts_pipeline = pipeline(
\n task=Tasks.text_to_speech,
\n model='damo\/speech_sambert-hifigan_tts_zh-cn_16k')<\/p>\n
def synthesize(self, text, emotion='neutral'):
\n try:
\n # \u6ce8\u610f：emotion\u53c2\u6570\u9700\u6839\u636e\u5b9e\u9645\u652f\u6301\u7684\u60c5\u611f\u7c7b\u578b\u8c03\u6574
\n result = self.tts_pipeline(input=text, voice='meina')<\/p>\n
# \u8fd4\u56de\u97f3\u9891\u6570\u636e（numpy array）\u548c\u91c7\u6837\u7387
\n wav_data = result['output_wav']
\n return wav_data
\n except Exception as e:
\n raise RuntimeError(f"\u5408\u6210\u5931\u8d25: {str(e)}")<\/p>\n
📌 \u8bf4\u660e：voice='meina' \u8868\u793a\u4f7f\u7528\u5973\u6027\u97f3\u8272\u201c\u7f8e\u5a1c\u201d，ModelScope\u5f53\u524d\u7248\u672c\u4e3b\u8981\u901a\u8fc7voice\u5b57\u6bb5\u95f4\u63a5\u63a7\u5236\u60c5\u611f\u503e\u5411\u3002<\/p>\n
🌐 Flask\u670d\u52a1\u4e3b\u7a0b\u5e8f（app.py）<\/h4>\n
# app.py
\nfrom flask import Flask, request, render_template, jsonify, send_file
\nimport os
\nimport time
\nimport numpy as np
\nfrom tts_engine import TTSProcessor<\/p>\n
app = Flask(__name__)
\nprocessor = TTSProcessor()<\/p>\n
AUDIO_DIR = '\/app\/static\/audio'
\nos.makedirs(AUDIO_DIR, exist_ok=True)<\/p>\n
@app.route('\/')
\ndef index():
\n return render_template('index.html')<\/p>\n
@app.route('\/api\/tts', methods=['POST'])
\ndef api_tts():
\n data = request.get_json()
\n text = data.get('text', '').strip()
\n emotion = data.get('emotion', 'neutral')<\/p>\n
if not text:
\n return jsonify({"status": "error", "message": "\u6587\u672c\u4e0d\u80fd\u4e3a\u7a7a"}), 400<\/p>\n
try:
\n wav_data = processor.synthesize(text, emotion)<\/p>\n
# \u751f\u6210\u552f\u4e00\u6587\u4ef6\u540d
\n timestamp = int(time.time())
\n filename = f"output_{timestamp}.wav"
\n filepath = os.path.join(AUDIO_DIR, filename)<\/p>\n
# \u4fdd\u5b58\u4e3awav\u6587\u4ef6
\n from scipy.io.wavfile import write
\n write(filepath, 16000, (wav_data * 32767).astype(np.int16))<\/p>\n
# \u6e05\u7406\u65e7\u6587\u4ef6（\u4fdd\u7559\u6700\u591a10\u4e2a）
\n files = sorted([f for f in os.listdir(AUDIO_DIR) if f.endswith('.wav')])
\n for old_file in files[:-10]:
\n os.remove(os.path.join(AUDIO_DIR, old_file))<\/p>\n
return jsonify({
\n "status": "success",
\n "audio_url": f"\/static\/audio\/{filename}",
\n "duration": len(wav_data) \/ 16000
\n })
\n except Exception as e:
\n return jsonify({"status": "error", "message": str(e)}), 500<\/p>\n
@app.route('\/static\/audio\/<filename>')
\ndef serve_audio(filename):
\n return send_file(os.path.join(AUDIO_DIR, filename))<\/p>\n
if __name__ == '__main__':
\n app.run(host='0.0.0.0', port=5000, threaded=True)<\/p>\n
🖼\ufe0f \u524d\u7aef\u9875\u9762\u903b\u8f91（templates\/index.html）<\/h4>\n
<!DOCTYPE html>
\n<html>
\n<head>
\n <title>Sambert-Hifigan \u8bed\u97f3\u5408\u6210<\/title>
\n <style>
\n body { font-family: Arial, sans-serif; margin: 40px; }
\n textarea { width: 100%; height: 120px; margin: 10px 0; }
\n button { padding: 10px 20px; font-size: 16px; }
\n audio { margin: 20px 0; }
\n <\/style>
\n<\/head>
\n<body>
\n <h1>🎙\ufe0f \u4e2d\u6587\u8bed\u97f3\u5408\u6210\u670d\u52a1<\/h1>
\n <p>\u8f93\u5165\u4efb\u610f\u4e2d\u6587\u6587\u672c，\u4f53\u9a8c\u9ad8\u8d28\u91cf\u8bed\u97f3\u5408\u6210\u3002<\/p>
\n <textarea id="textInput" placeholder="\u8bf7\u8f93\u5165\u8981\u5408\u6210\u7684\u4e2d\u6587\u6587\u672c…"><\/textarea><br\/>
\n <button onclick="synthesize()">\u5f00\u59cb\u5408\u6210\u8bed\u97f3<\/button>
\n <div id="result"><\/div><\/p>\n
<script>
\n function synthesize() {
\n const text = document.getElementById('textInput').value;
\n if (!text) {
\n alert("\u8bf7\u8f93\u5165\u6587\u672c！");
\n return;
\n }<\/p>\n
fetch('\/api\/tts', {
\n method: 'POST',
\n headers: { 'Content-Type': 'application\/json' },
\n body: JSON.stringify({ text: text, emotion: 'neutral' })
\n })
\n .then(res => res.json())
\n .then(data => {
\n if (data.status === 'success') {
\n const audioUrl = data.audio_url + '?t=' + new Date().getTime();
\n document.getElementById('result').innerHTML = `
\n <p>\u5408\u6210\u5b8c\u6210（\u8017\u65f6 ${data.duration.toFixed(1)} \u79d2）：<\/p>
\n <audio controls src="${audioUrl}"><\/audio><br\/>
\n <a href="${audioUrl}" download>📥 \u4e0b\u8f7d\u97f3\u9891<\/a>
\n `;
\n } else {
\n document.getElementById('result').innerHTML =
\n `<p style="color:red;">\u9519\u8bef：${data.message}<\/p>`;
\n }
\n })
\n .catch(err => {
\n console.error(err);
\n alert("\u8bf7\u6c42\u5931\u8d25，\u8bf7\u68c0\u67e5\u7f51\u7edc\u6216\u670d\u52a1\u72b6\u6001\u3002");
\n });
\n }
\n <\/script>
\n<\/body>
\n<\/html><\/p>\n
\n
\u6027\u80fd\u4f18\u5316\u4e0e\u7a33\u5b9a\u6027\u4fdd\u969c<\/h3>\n
\u4e3a\u4e86\u8ba9\u670d\u52a1\u57284\u6838CPU\u4e0a\u957f\u671f\u7a33\u5b9a\u8fd0\u884c，\u6211\u4eec\u8fdb\u884c\u4e86\u591a\u9879\u5173\u952e\u4f18\u5316：<\/p>\n
🔧 \u4f9d\u8d56\u7248\u672c\u9501\u5b9a（requirements.txt\u8282\u9009）<\/h4>\n
modelscope==1.13.0
\ntorch==1.13.1+cpu
\nscipy==1.10.1
\nnumpy==1.23.5
\nflask==2.3.3<\/p>\n
\u26a0\ufe0f \u91cd\u8981\u4fee\u590d：\u65e9\u671f\u7248\u672c\u4e2d datasets>=2.13.0 \u4f1a\u5f3a\u5236\u5347\u7ea7 numpy>=1.24.0，\u800c scipy<1.13 \u4e0d\u517c\u5bb9\u8be5\u7248\u672c，\u5bfc\u81f4ImportError\u3002\u901a\u8fc7\u663e\u5f0f\u6307\u5b9a numpy==1.23.5 \u6210\u529f\u89c4\u907f\u6b64\u95ee\u9898\u3002<\/p>\n
\u2699\ufe0f CPU\u63a8\u7406\u4f18\u5316\u6280\u5de7<\/h4>\n
\u542f\u7528ONNX Runtime（\u53ef\u9009）
\n \u5c06Hifi-GAN\u5bfc\u51fa\u4e3aONNX\u683c\u5f0f，\u5229\u7528ORT\u7684CPU\u4f18\u5316\u5185\u6838\u63d0\u5347\u89e3\u7801\u901f\u5ea6\u7ea620%\u3002<\/p>\n<\/li>\n
\u7ebf\u7a0b\u6570\u8c03\u4f18
\n \u8bbe\u7f6e OMP_NUM_THREADS=4 \u548c MKL_NUM_THREADS=4，\u5145\u5206\u5229\u7528\u591a\u6838\u5e76\u884c\u8ba1\u7b97\u80fd\u529b\u3002<\/p>\n<\/li>\n
\u7981\u7528\u68af\u5ea6\u8ba1\u7b97
\n \u6240\u6709\u63a8\u7406\u8fc7\u7a0b\u5747\u5305\u88f9\u5728 with torch.no_grad(): \u4e2d，\u51cf\u5c11\u5185\u5b58\u5f00\u9500\u3002<\/p>\n<\/li>\n
\u6a21\u578b\u5e38\u9a7b\u5185\u5b58
\n Flask\u5e94\u7528\u542f\u52a8\u65f6\u4e00\u6b21\u6027\u52a0\u8f7d\u6a21\u578b，\u907f\u514d\u91cd\u590d\u521d\u59cb\u5316\u5e26\u6765\u7684\u5ef6\u8fdf\u3002<\/p>\n<\/li>\n
\n
\u5e94\u7528\u573a\u666f\u4e0e\u6269\u5c55\u5efa\u8bae<\/h3>\n🎯 \u5178\u578b\u9002\u7528\u573a\u666f<\/h4>\n\n- \u4f01\u4e1aIVR\u8bed\u97f3\u5bfc\u822a：\u81ea\u52a8\u751f\u6210\u52a8\u6001\u64ad\u62a5\u5185\u5bb9<\/li>\n
- \u65e0\u969c\u788d\u9605\u8bfb\u5de5\u5177：\u4e3a\u89c6\u969c\u7528\u6237\u63d0\u4f9b\u7f51\u9875\u6717\u8bfb\u529f\u80fd<\/li>\n
- \u6559\u80b2\u7c7b\u4ea7\u54c1：\u5236\u4f5c\u5e26\u60c5\u611f\u7684\u8bfe\u6587\u6717\u8bfb\u97f3\u9891<\/li>\n
- \u77ed\u89c6\u9891\u914d\u97f3：\u5feb\u901f\u751f\u6210\u5e26\u60c5\u7eea\u53d8\u5316\u7684\u65c1\u767d<\/li>\n<\/ul>\n
🔄 \u6269\u5c55\u65b9\u5411\u5efa\u8bae<\/h4>\n
- \n
\u589e\u52a0\u60c5\u611f\u63a7\u5236\u7c92\u5ea6
\n \u7ed3\u5408\u5916\u90e8\u60c5\u611f\u5206\u6790\u6a21\u578b，\u5b9e\u73b0\u201c\u8f93\u5165\u6587\u672c \u2192 \u81ea\u52a8\u8bc6\u522b\u60c5\u611f \u2192 \u5339\u914d\u97f3\u8272\u201d\u7684\u95ed\u73af\u3002<\/p>\n<\/li>\n
- \n
\u652f\u6301\u591a\u97f3\u8272\u5207\u6362
\n \u52a0\u8f7d\u591a\u4e2a\u9884\u8bad\u7ec3voice\u6a21\u578b（\u5982\u7537\u58f0\u3001\u7ae5\u58f0），\u901a\u8fc7API\u53c2\u6570\u52a8\u6001\u9009\u62e9\u3002<\/p>\n<\/li>\n
- \n
\u63a5\u5165\u6d41\u5f0f\u4f20\u8f93
\n \u5bf9\u957f\u6587\u672c\u5206\u6bb5\u5408\u6210，\u914d\u5408WebSocket\u5b9e\u73b0\u8fb9\u751f\u6210\u8fb9\u64ad\u653e\u3002<\/p>\n<\/li>\n
- \n
\u90e8\u7f72\u81f3\u8fb9\u7f18\u8bbe\u5907
\n \u8fdb\u4e00\u6b65\u88c1\u526a\u6a21\u578b\u89c4\u6a21，\u9002\u914d\u6811\u8393\u6d3e\u6216\u56fd\u4ea7\u5316ARM\u5e73\u53f0\u3002<\/p>\n<\/li>\n
\n\u603b\u7ed3：\u4f4e\u6210\u672c\u4e5f\u80fd\u5b9e\u73b0\u9ad8\u8d28\u91cf\u8bed\u97f3\u5408\u6210<\/h3>\n
\u672c\u6587\u4ecb\u7ecd\u4e86\u4e00\u79cd\u57fa\u4e8e ModelScope Sambert-Hifigan \u7684\u8f7b\u91cf\u7ea7\u4e2d\u6587\u591a\u60c5\u611f\u8bed\u97f3\u5408\u6210\u65b9\u6848，\u5177\u5907\u4ee5\u4e0b\u6838\u5fc3\u4ef7\u503c：<\/p>\n
\u2705 \u6210\u672c\u4f4e：\u65e0\u9700GPU，4\u6838CPU\u5373\u53ef\u7a33\u5b9a\u8fd0\u884c
\n\u2705 \u6613\u90e8\u7f72：Docker\u955c\u50cf\u5c01\u88c5，\u4f9d\u8d56\u5168\u89e3\u51b3，\u62d2\u7edd\u73af\u5883\u62a5\u9519
\n\u2705 \u529f\u80fd\u5168：\u540c\u65f6\u63d0\u4f9bWebUI\u4e0eAPI，\u6ee1\u8db3\u6f14\u793a\u4e0e\u96c6\u6210\u53cc\u91cd\u9700\u6c42
\n\u2705 \u8d28\u91cf\u9ad8：\u652f\u6301\u591a\u60c5\u611f\u3001\u9ad8\u4fdd\u771f\u97f3\u9891\u8f93\u51fa，\u9002\u7528\u4e8e\u751f\u4ea7\u73af\u5883 <\/p>\n
\u901a\u8fc7Flask\u670d\u52a1\u5c01\u88c5，\u6211\u4eec\u5c06\u590d\u6742\u7684\u6a21\u578b\u63a8\u7406\u8f6c\u5316\u4e3a\u7b80\u5355\u7684\u6587\u672c\u8f93\u5165\u4e0e\u97f3\u9891\u8f93\u51fa，\u771f\u6b63\u5b9e\u73b0\u4e86\u201c\u8ba9AI\u8bed\u97f3\u89e6\u624b\u53ef\u53ca\u201d\u3002<\/p>\n
\u672a\u6765，\u968f\u7740\u6a21\u578b\u538b\u7f29\u6280\u672f\u548cCPU\u7b97\u5b50\u4f18\u5316\u7684\u6301\u7eed\u8fdb\u6b65，\u8fd9\u7c7b\u7eafCPU\u9a71\u52a8\u7684\u9ad8\u8d28\u91cfTTS\u670d\u52a1\u5c06\u5728\u66f4\u591a\u8fb9\u7f18\u573a\u666f\u4e2d\u53d1\u6325\u91cd\u8981\u4f5c\u7528\u3002\u5bf9\u4e8e\u8ffd\u6c42\u6027\u4ef7\u6bd4\u7684\u6280\u672f\u56e2\u961f\u6765\u8bf4，\u8fd9\u65e0\u7591\u662f\u4e00\u6761\u503c\u5f97\u6df1\u5165\u63a2\u7d22\u7684\u843d\u5730\u8def\u5f84\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
\u4f4e\u6210\u672c\u8bed\u97f3\u89e3\u51b3\u65b9\u6848：Sambert-Hifigan\u53ef\u57284\u6838CPU\u670d\u52a1\u5668\u7a33\u5b9a\u8fd0\u884c
\n\u5f15\u8a00：\u4e2d\u6587\u591a\u60c5\u611f\u8bed\u97f3\u5408\u6210\u7684\u73b0\u5b9e\u9700\u6c42
\n\u968f\u7740\u667a\u80fd\u5ba2\u670d\u3001\u6709\u58f0\u9605\u8bfb\u3001\u865a\u62df\u4e3b\u64ad\u7b49\u5e94\u7528\u573a\u666f\u7684\u666e\u53ca，\u9ad8\u8d28\u91cf\u7684\u4e2d\u6587\u591a\u60c5\u611f\u8bed\u97f3\u5408\u6210（TTS） \u5df2\u6210\u4e3aAI\u843d\u5730\u7684\u91cd\u8981\u4e00\u73af\u3002\u4f20\u7edf\u65b9\u6848\u5f80\u5f80\u4f9d\u8d56GPU\u52a0\u901f\u6216\u6602\u8d35\u7684\u4e91\u670d\u52a1，\u5bfc\u81f4\u90e8\u7f72\u6210\u672c\u9ad8\u3001\u8fd0\u7ef4\u590d\u6742\u3002\u5bf9\u4e8e\u4e2d\u5c0f\u4f01\u4e1a\u548c\u8fb9\u7f18\u573a\u666f\u800c\u8a00，\u4e9f\u9700\u4e00\u79cd\u4f4e\u6210\u672c\u3001\u6613\u90e8\u7f72\u3001\u6027\u80fd\u7a33\u5b9a\u7684\u66ff\u4ee3\u65b9\u6848\u3002
\nModel<\/p>\n","protected":false},"author":2,"featured_media":59803,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"topic":[],"class_list":["post-59804","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server"],"yoast_head":"\n
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🔄 \u6269\u5c55\u65b9\u5411\u5efa\u8bae<\/h4>\n
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\n \u5bf9\u957f\u6587\u672c\u5206\u6bb5\u5408\u6210，\u914d\u5408WebSocket\u5b9e\u73b0\u8fb9\u751f\u6210\u8fb9\u64ad\u653e\u3002<\/p>\n<\/li>\n - \n
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\u672c\u6587\u4ecb\u7ecd\u4e86\u4e00\u79cd\u57fa\u4e8e ModelScope Sambert-Hifigan \u7684\u8f7b\u91cf\u7ea7\u4e2d\u6587\u591a\u60c5\u611f\u8bed\u97f3\u5408\u6210\u65b9\u6848，\u5177\u5907\u4ee5\u4e0b\u6838\u5fc3\u4ef7\u503c：<\/p>\n
\u2705 \u6210\u672c\u4f4e：\u65e0\u9700GPU，4\u6838CPU\u5373\u53ef\u7a33\u5b9a\u8fd0\u884c
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