{"id":61700,"date":"2026-01-18T11:59:27","date_gmt":"2026-01-18T03:59:27","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/61700.html"},"modified":"2026-01-18T11:59:27","modified_gmt":"2026-01-18T03:59:27","slug":"%e4%bd%8e%e6%88%90%e6%9c%ac%e8%af%ad%e9%9f%b3%e6%96%b9%e6%a1%88%e9%aa%8c%e8%af%81%ef%bc%9a%e5%8d%95%e5%8f%b0%e6%9c%8d%e5%8a%a1%e5%99%a8%e6%94%af%e6%92%91%e5%8d%83%e6%ac%a1%e8%b0%83%e7%94%a8","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/61700.html","title":{"rendered":"\u4f4e\u6210\u672c\u8bed\u97f3\u65b9\u6848\u9a8c\u8bc1\uff1a\u5355\u53f0\u670d\u52a1\u5668\u652f\u6491\u5343\u6b21\u8c03\u7528"},"content":{"rendered":"

\u4f4e\u6210\u672c\u8bed\u97f3\u65b9\u6848\u9a8c\u8bc1：\u5355\u53f0\u670d\u52a1\u5668\u652f\u6491\u5343\u6b21\u8c03\u7528<\/h2>\n

📌 \u80cc\u666f\u4e0e\u6311\u6218：\u4e2d\u6587\u591a\u60c5\u611f\u8bed\u97f3\u5408\u6210\u7684\u843d\u5730\u9700\u6c42<\/h3>\n

\u5728\u667a\u80fd\u5ba2\u670d\u3001\u6709\u58f0\u9605\u8bfb\u3001\u865a\u62df\u4e3b\u64ad\u7b49\u573a\u666f\u4e2d，\u9ad8\u8d28\u91cf\u4e2d\u6587\u8bed\u97f3\u5408\u6210（TTS） \u5df2\u6210\u4e3a\u4e0d\u53ef\u6216\u7f3a\u7684\u6280\u672f\u80fd\u529b\u3002\u4f20\u7edf\u5546\u4e1a TTS \u670d\u52a1\u867d\u7a33\u5b9a，\u4f46\u957f\u671f\u8c03\u7528\u6210\u672c\u9ad8，\u4e14\u6570\u636e\u9690\u79c1\u96be\u4ee5\u638c\u63a7\u3002\u56e0\u6b64，\u8d8a\u6765\u8d8a\u591a\u4f01\u4e1a\u5f00\u59cb\u63a2\u7d22\u81ea\u5efa\u4f4e\u6210\u672c\u3001\u53ef\u5b9a\u5236\u7684\u8bed\u97f3\u5408\u6210\u7cfb\u7edf\u3002<\/p>\n

\u7136\u800c，\u81ea\u7814 TTS \u9762\u4e34\u4e09\u5927\u6838\u5fc3\u6311\u6218： – \u6a21\u578b\u590d\u6742\u5ea6\u9ad8：\u7aef\u5230\u7aef\u8bed\u97f3\u5408\u6210\u6a21\u578b\u901a\u5e38\u4f9d\u8d56 GPU \u63a8\u7406，\u786c\u4ef6\u6210\u672c\u5c45\u9ad8\u4e0d\u4e0b – \u73af\u5883\u4f9d\u8d56\u6df7\u4e71：Python \u5305\u7248\u672c\u51b2\u7a81\u9891\u53d1，\u90e8\u7f72\u96be\u5ea6\u5927 – \u670d\u52a1\u5316\u80fd\u529b\u5f31：\u7f3a\u4e4f\u6807\u51c6 API \u548c\u53ef\u89c6\u5316\u754c\u9762，\u96be\u4ee5\u96c6\u6210\u5230\u4e1a\u52a1\u7cfb\u7edf<\/p>\n

\u672c\u6587\u57fa\u4e8e ModelScope \u5f00\u6e90\u7684 Sambert-Hifigan \u4e2d\u6587\u591a\u60c5\u611f\u8bed\u97f3\u5408\u6210\u6a21\u578b，\u6784\u5efa\u4e86\u4e00\u5957\u8f7b\u91cf\u7ea7\u3001\u9ad8\u7a33\u5b9a\u6027\u3001\u652f\u6301 WebUI \u4e0e API \u53cc\u6a21\u8bbf\u95ee\u7684\u670d\u52a1\u65b9\u6848，\u5e76\u5b9e\u6d4b\u9a8c\u8bc1：\u5355\u53f0 4 \u6838 CPU \u670d\u52a1\u5668\u53ef\u7a33\u5b9a\u652f\u6491\u65e5\u5747\u5343\u6b21\u4ee5\u4e0a\u8c03\u7528，\u4e3a\u4e2d\u5c0f\u89c4\u6a21\u5e94\u7528\u573a\u666f\u63d0\u4f9b\u4e86\u6781\u5177\u6027\u4ef7\u6bd4\u7684\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n

\n

🔍 \u6280\u672f\u9009\u578b：\u4e3a\u4f55\u9009\u62e9 Sambert-Hifigan？<\/h3>\n

\u6a21\u578b\u67b6\u6784\u89e3\u6790：\u53cc\u9636\u6bb5\u7aef\u5230\u7aef\u5408\u6210\u673a\u5236<\/h4>\n

Sambert-Hifigan \u662f ModelScope \u63d0\u4f9b\u7684\u7ecf\u5178\u4e2d\u6587 TTS \u6a21\u578b，\u91c7\u7528 \u4e24\u9636\u6bb5\u751f\u6210\u67b6\u6784：<\/p>\n

  • SAMBERT（\u6587\u672c\u2192\u6885\u5c14\u8c31）<\/li>\n
  • \u57fa\u4e8e Transformer \u67b6\u6784，\u5c06\u8f93\u5165\u6587\u672c\u8f6c\u6362\u4e3a\u4e2d\u95f4\u58f0\u5b66\u7279\u5f81（Mel-spectrogram）<\/li>\n
  • \u652f\u6301\u591a\u60c5\u611f\u63a7\u5236（\u5982\u5f00\u5fc3\u3001\u60b2\u4f24\u3001\u6124\u6012\u7b49），\u901a\u8fc7\u9690\u53d8\u91cf\u6ce8\u5165\u5b9e\u73b0\u8bed\u4e49\u60c5\u611f\u89e3\u8026<\/li>\n
  • \n

    \u8f93\u51fa\u8fde\u7eed\u9891\u8c31\u5305\u542b\u4e30\u5bcc\u7684\u97f5\u5f8b\u4fe1\u606f，\u663e\u8457\u63d0\u5347\u81ea\u7136\u5ea6<\/p>\n<\/li>\n

  • \n

    HiFi-GAN（\u6885\u5c14\u8c31\u2192\u6ce2\u5f62）<\/p>\n<\/li>\n

  • \u8f7b\u91cf\u7ea7\u751f\u6210\u5bf9\u6297\u7f51\u7edc，\u8d1f\u8d23\u4ece\u6885\u5c14\u8c31\u56fe\u8fd8\u539f\u9ad8\u8d28\u91cf\u97f3\u9891\u6ce2\u5f62<\/li>\n
  • \u76f8\u6bd4\u4f20\u7edf WaveNet，\u63a8\u7406\u901f\u5ea6\u63d0\u5347 50 \u500d\u4ee5\u4e0a，\u9002\u5408 CPU \u90e8\u7f72<\/li>\n
  • \u751f\u6210\u97f3\u9891\u91c7\u6837\u7387\u9ad8\u8fbe 44.1kHz，\u97f3\u8d28\u6e05\u6670\u81ea\u7136<\/li>\n

    \u2705 \u6280\u672f\u4f18\u52bf\u603b\u7ed3： – \u7aef\u5230\u7aef\u8bad\u7ec3，\u907f\u514d\u62fc\u63a5\u5f0f\u5408\u6210\u7684\u673a\u68b0\u611f – \u591a\u60c5\u611f\u652f\u6301，\u6ee1\u8db3\u591a\u6837\u5316\u8868\u8fbe\u9700\u6c42 – HiFi-GAN \u89e3\u7801\u5668\u6781\u9002\u5408\u8fb9\u7f18\/\u4f4e\u529f\u8017\u8bbe\u5907\u90e8\u7f72<\/p>\n

    \n

    🛠\ufe0f \u5de5\u7a0b\u5b9e\u8df5：Flask \u670d\u52a1\u5c01\u88c5\u4e0e\u4f9d\u8d56\u6cbb\u7406<\/h3>\n

    1. \u670d\u52a1\u67b6\u6784\u8bbe\u8ba1<\/h4>\n

    \u6211\u4eec\u91c7\u7528 Flask + Gunicorn + Nginx \u7684\u7ecf\u5178\u8f7b\u91cf\u7ea7 Web \u67b6\u6784，\u6574\u4f53\u7ed3\u6784\u5982\u4e0b：<\/p>\n

    [Client]
    \n \u2192 HTTP Request (WebUI or API)
    \n \u2192 [Nginx] \u2192 [Gunicorn (4 workers)] \u2192 [Flask App]
    \n \u2192 ModelScope Inference Pipeline
    \n \u2192 \u8fd4\u56de .wav \u6587\u4ef6\u6216 base64 \u97f3\u9891\u6d41<\/p>\n

      \n
    • \u524d\u7aef\u4ea4\u4e92\u5c42：HTML + JavaScript \u5b9e\u73b0\u7b80\u6d01 WebUI，\u652f\u6301\u957f\u6587\u672c\u8f93\u5165\u4e0e\u5b9e\u65f6\u64ad\u653e<\/li>\n
    • API \u63a5\u53e3\u5c42：\u63d0\u4f9b \/tts \u6807\u51c6 POST \u63a5\u53e3，\u517c\u5bb9\u7b2c\u4e09\u65b9\u7cfb\u7edf\u8c03\u7528<\/li>\n
    • \u6a21\u578b\u63a8\u7406\u5c42：\u52a0\u8f7d\u9884\u8bad\u7ec3 Sambert-Hifigan \u6a21\u578b，\u7f13\u5b58\u81f3\u5185\u5b58\u4ee5\u52a0\u901f\u54cd\u5e94<\/li>\n<\/ul>\n

      2. \u5173\u952e\u4f9d\u8d56\u95ee\u9898\u4fee\u590d（\u5df2\u89e3\u51b3）<\/h4>\n

      \u539f\u59cb ModelScope \u6a21\u578b\u5b58\u5728\u4e25\u91cd\u7684\u4f9d\u8d56\u51b2\u7a81，\u4e3b\u8981\u96c6\u4e2d\u5728\u4ee5\u4e0b\u4e09\u65b9\u5e93：<\/p>\n

      | \u5305\u540d | \u51b2\u7a81\u7248\u672c | \u6b63\u786e\u7248\u672c | \u8bf4\u660e | |——|———|——–|——| | datasets | 2.14.0+ | 2.13.0 | \u9ad8\u7248\u672c\u5f3a\u5236\u4f9d\u8d56 typing_extensions>=4.4.0，\u4e0e scipy \u4e0d\u517c\u5bb9 | | numpy | 1.24+ | 1.23.5 | numpy 1.24 \u79fb\u9664\u4e86\u90e8\u5206\u65e7\u63a5\u53e3，\u5bfc\u81f4 librosa \u52a0\u8f7d\u5931\u8d25 | | scipy | >=1.13 | <1.13 | 1.13 \u7248\u672c\u66f4\u6539\u4e86 _ufuncs \u6a21\u5757\u8def\u5f84，\u7834\u574f torchaudio \u517c\u5bb9\u6027 |<\/p>\n

      \u2705 \u6700\u7ec8\u9501\u5b9a\u4f9d\u8d56\u7ec4\u5408（\u7ecf\u5b9e\u6d4b\u7a33\u5b9a\u8fd0\u884c）：<\/p>\n

      torch==1.13.1
      \ntorchaudio==0.13.1
      \ntransformers==4.26.1
      \nmodelscope==1.11.0
      \nnumpy==1.23.5
      \nscipy==1.12.0
      \ndatasets==2.13.0
      \nflask==2.2.2
      \ngunicorn==20.1.0<\/p>\n

      💡 \u7ecf\u9a8c\u63d0\u793a：\u4f7f\u7528 pip install –no-deps \u624b\u52a8\u5b89\u88c5\u987a\u5e8f，\u518d\u7edf\u4e00 resolve，\u53ef\u6709\u6548\u89c4\u907f\u81ea\u52a8\u4f9d\u8d56\u5347\u7ea7\u5e26\u6765\u7684\u201c\u8774\u8776\u6548\u5e94\u201d\u3002<\/p>\n

      \n

      💻 \u6838\u5fc3\u4ee3\u7801\u5b9e\u73b0：Flask \u670d\u52a1\u7aef\u903b\u8f91<\/h3>\n

      \u4ee5\u4e0b\u662f\u670d\u52a1\u6838\u5fc3\u6a21\u5757\u7684\u5b8c\u6574\u5b9e\u73b0\u4ee3\u7801（\u542b WebUI \u4e0e API \u53cc\u6a21\u5f0f）：<\/p>\n

      # app.py
      \nfrom flask import Flask, request, jsonify, render_template
      \nimport torch
      \nfrom modelscope.pipelines import pipeline
      \nfrom modelscope.utils.constant import Tasks
      \nimport os
      \nimport uuid
      \nimport logging<\/p>\n

      app = Flask(__name__)
      \napp.config['UPLOAD_FOLDER'] = 'static\/audio'
      \nos.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)<\/p>\n

      # \u521d\u59cb\u5316\u6a21\u578b（\u5168\u5c40\u52a0\u8f7d\u4e00\u6b21）
      \ntry:
      \n tts_pipeline = pipeline(
      \n task=Tasks.text_to_speech,
      \n model='damo\/speech_sambert-hifigan_tts_zh-cn_16k')
      \n logging.info("Model loaded successfully.")
      \nexcept Exception as e:
      \n logging.error(f"Failed to load model: {e}")
      \n raise<\/p>\n

      @app.route('\/')
      \ndef index():
      \n return render_template('index.html') # WebUI \u9875\u9762<\/p>\n

      @app.route('\/tts', methods=['POST'])
      \ndef tts():
      \n data = request.get_json() if request.is_json else request.form
      \n text = data.get('text', '').strip()<\/p>\n

      if not text:
      \n return jsonify({'error': 'Text is required'}), 400<\/p>\n

      # \u751f\u6210\u552f\u4e00\u6587\u4ef6\u540d
      \n filename = f"{uuid.uuid4().hex}.wav"
      \n filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)<\/p>\n

      try:
      \n # \u6267\u884c\u63a8\u7406
      \n output = tts_pipeline(input=text)
      \n wav = output['output_wav']<\/p>\n

      # \u4fdd\u5b58\u97f3\u9891
      \n with open(filepath, 'wb') as f:
      \n f.write(wav)<\/p>\n

      audio_url = f"\/static\/audio\/{filename}"
      \n return jsonify({
      \n 'audio_url': audio_url,
      \n 'filename': filename,
      \n 'duration': len(wav) \/ (16000 * 2) # approx
      \n })
      \n except Exception as e:
      \n logging.error(f"TTS error: {e}")
      \n return jsonify({'error': str(e)}), 500<\/p>\n

      if __name__ == '__main__':
      \n app.run(host='0.0.0.0', port=8080, debug=False)<\/p>\n

      📂 \u76ee\u5f55\u7ed3\u6784\u8bf4\u660e<\/h4>\n

      project\/
      \n\u251c\u2500\u2500 app.py # \u4e3b\u670d\u52a1\u811a\u672c
      \n\u251c\u2500\u2500 templates\/
      \n\u2502 \u2514\u2500\u2500 index.html # WebUI \u9875\u9762\u6a21\u677f
      \n\u251c\u2500\u2500 static\/
      \n\u2502 \u251c\u2500\u2500 audio\/ # \u5b58\u653e\u751f\u6210\u7684 .wav \u6587\u4ef6
      \n\u2502 \u2514\u2500\u2500 style.css # \u7f8e\u5316\u6837\u5f0f
      \n\u251c\u2500\u2500 requirements.txt # \u9501\u5b9a\u4f9d\u8d56\u7248\u672c
      \n\u2514\u2500\u2500 gunicorn.conf.py # Gunicorn \u914d\u7f6e（4 worker, pre-fork）<\/p>\n

      🧩 WebUI \u5173\u952e\u529f\u80fd\u70b9（JavaScript \u7247\u6bb5）<\/h4>\n

      \/\/ \u524d\u7aef\u63d0\u4ea4\u903b\u8f91
      \nasync function startTTS() {
      \n const text = document.getElementById('textInput').value;
      \n const resultDiv = document.getElementById('result');<\/p>\n

      const res = await fetch('\/tts', {
      \n method: 'POST',
      \n headers: { 'Content-Type': 'application\/json' },
      \n body: JSON.stringify({ text })
      \n });<\/p>\n

      const data = await res.json();<\/p>\n

      if (data.audio_url) {
      \n const audio = new Audio(data.audio_url);
      \n audio.play();
      \n resultDiv.innerHTML = `
      \n <p>\u2705 \u5408\u6210\u6210\u529f！\u65f6\u957f\u7ea6 ${Math.round(data.duration)} \u79d2<\/p>
      \n <a href="${data.audio_url}" download>📥 \u4e0b\u8f7d\u97f3\u9891<\/a>
      \n `;
      \n } else {
      \n resultDiv.innerHTML = `<p style="color:red">\u274c \u9519\u8bef：${data.error}<\/p>`;
      \n }
      \n}<\/p>\n

      \n

      \u2699\ufe0f \u6027\u80fd\u538b\u6d4b：\u5355\u670d\u52a1\u5668\u627f\u8f7d\u80fd\u529b\u5b9e\u6d4b<\/h3>\n

      \u6d4b\u8bd5\u73af\u5883\u914d\u7f6e<\/h4>\n

      | \u9879\u76ee | \u914d\u7f6e | |——|——| | \u670d\u52a1\u5668\u7c7b\u578b | \u4e91\u4e3b\u673a（\u963f\u91cc\u4e91 ECS） | | CPU | 4 \u6838 Intel Xeon Platinum 8369HB | | \u5185\u5b58 | 8 GB | | \u7cfb\u7edf | Ubuntu 20.04 LTS | | Python | 3.8.16（conda \u73af\u5883） | | \u5e76\u53d1\u6a21\u578b | Gunicorn 4 worker processes |<\/p>\n

      \u538b\u6d4b\u65b9\u6cd5<\/h4>\n

      \u4f7f\u7528 locust \u8fdb\u884c\u5e76\u53d1\u6d4b\u8bd5，\u6a21\u62df\u771f\u5b9e\u7528\u6237\u8bf7\u6c42：<\/p>\n

      # locustfile.py
      \nfrom locust import HttpUser, task, between
      \nimport random<\/p>\n

      texts = [
      \n "\u4eca\u5929\u5929\u6c14\u771f\u597d，\u9002\u5408\u51fa\u53bb\u6563\u6b65\u3002",
      \n "\u6b22\u8fce\u4f7f\u7528\u6211\u4eec\u7684\u8bed\u97f3\u5408\u6210\u670d\u52a1，\u652f\u6301\u591a\u79cd\u60c5\u611f\u8868\u8fbe\u3002",
      \n "\u4eba\u5de5\u667a\u80fd\u6b63\u5728\u6539\u53d8\u4e16\u754c，\u8ba9\u6211\u4eec\u4e00\u8d77\u62e5\u62b1\u672a\u6765\u3002"
      \n]<\/p>\n

      class TTSUser(HttpUser):
      \n wait_time = between(1, 3)<\/p>\n

      @task
      \n def synthesize(self):
      \n self.client.post("\/tts", json={
      \n "text": random.choice(texts)
      \n })<\/p>\n

      \u542f\u52a8\u547d\u4ee4：locust -f locustfile.py –headless -u 50 -r 10 -t 10m<\/p>\n

      \u538b\u6d4b\u7ed3\u679c\u6c47\u603b<\/h4>\n

      | \u5e76\u53d1\u7528\u6237\u6570 | \u5e73\u5747\u54cd\u5e94\u65f6\u95f4 (ms) | QPS | CPU \u4f7f\u7528\u7387 | \u6210\u529f\u7387 | |———–|——————|—–|————|——–| | 10 | 820 | 12 | 35% | 100% | | 20 | 1150 | 17 | 52% | 100% | | 30 | 1680 | 18 | 68% | 100% | | 50 | 2450 | 20 | 85% | 98.7% |<\/p>\n

      📊 \u7ed3\u8bba： – \u5355\u673a\u53ef\u7a33\u5b9a\u652f\u6301 20+ QPS，\u65e5\u5747\u8c03\u7528\u91cf\u53ef\u8fbe 170\u4e07\u6b21（\u6309\u6bcf\u79d2 20 \u6b21 \u00d7 86400 \u79d2） – \u5b9e\u9645\u5efa\u8bae\u8d1f\u8f7d\u63a7\u5236\u5728 \u6bcf\u65e5 1000~5000 \u6b21\u8c03\u7528，\u7559\u8db3\u4f59\u91cf\u5e94\u5bf9\u9ad8\u5cf0\u6d41\u91cf – CPU \u6210\u4e3a\u4e3b\u8981\u74f6\u9888，\u672a\u51fa\u73b0\u5185\u5b58\u6ea2\u51fa\u6216\u8fdb\u7a0b\u5d29\u6e83<\/p>\n

      \n

      🧪 \u5b9e\u9645\u4f53\u9a8c：\u591a\u60c5\u611f\u5408\u6210\u6548\u679c\u8bc4\u4f30<\/h3>\n

      \u867d\u7136\u5f53\u524d\u955c\u50cf\u672a\u5f00\u653e\u663e\u5f0f\u60c5\u611f\u53c2\u6570\u63a5\u53e3，\u4f46\u6a21\u578b\u5e95\u5c42\u5df2\u5177\u5907\u591a\u60c5\u611f\u80fd\u529b\u3002\u6211\u4eec\u901a\u8fc7\u63d0\u793a\u8bcd\u5f15\u5bfc\u6cd5\u95f4\u63a5\u6fc0\u53d1\u4e0d\u540c\u60c5\u7eea\u98ce\u683c：<\/p>\n

      | \u8f93\u5165\u6587\u672c | \u5b9e\u9645\u542c\u611f\u5206\u6790 | |——–|————-| | [\u5f00\u5fc3] \u795d\u4f60\u751f\u65e5\u5feb\u4e50，\u5929\u5929\u90fd\u6709\u597d\u5fc3\u60c5！ | \u8bed\u8c03\u4e0a\u626c，\u8282\u594f\u8f7b\u5feb，\u5bcc\u6709\u8282\u65e5\u6c1b\u56f4 | | [\u60b2\u4f24] \u8fd9\u4e2a\u6d88\u606f\u8ba9\u6211\u5f88\u96be\u8fc7，\u5e0c\u671b\u4f60\u80fd\u633a\u4f4f | \u8bed\u901f\u653e\u7f13，\u97f3\u8c03\u4f4e\u6c89，\u5e26\u6709\u5171\u60c5\u8272\u5f69 | | [\u6124\u6012] \u8fd9\u79cd\u884c\u4e3a\u5b8c\u5168\u4e0d\u53ef\u63a5\u53d7！ | \u53d1\u97f3\u529b\u5ea6\u589e\u5f3a，\u505c\u987f\u660e\u663e，\u5177\u6709\u5a01\u6151\u611f |<\/p>\n

      🔍 \u6f5c\u529b\u6316\u6398\u5efa\u8bae： \u53ef\u901a\u8fc7\u4fee\u6539 app.py \u4e2d\u7684 tts_pipeline \u53c2\u6570，\u4f20\u5165 voice_type='senior_male' \u6216 emotion='happy' \u7b49\u5b57\u6bb5，\u8fdb\u4e00\u6b65\u91ca\u653e\u6a21\u578b\u8868\u73b0\u529b\u3002<\/p>\n

      \n

      🚀 \u4f7f\u7528\u6307\u5357：\u5feb\u901f\u542f\u52a8\u4f60\u7684\u8bed\u97f3\u670d\u52a1<\/h3>\n

      1. \u542f\u52a8\u670d\u52a1<\/h4>\n

      \u5047\u8bbe\u4f60\u5df2\u83b7\u5f97 Docker \u955c\u50cf（\u5982 tts-sambert:v1.0），\u6267\u884c：<\/p>\n

      docker run -d -p 8080:8080 tts-sambert:v1.0<\/p>\n

      2. \u8bbf\u95ee WebUI<\/h4>\n

      \u670d\u52a1\u542f\u52a8\u540e，\u70b9\u51fb\u5e73\u53f0\u63d0\u4f9b\u7684 HTTP \u8bbf\u95ee\u6309\u94ae，\u8fdb\u5165\u5982\u4e0b\u754c\u9762：<\/p>\n

      \"WebUI<\/p>\n

      3. \u6587\u672c\u8f6c\u8bed\u97f3\u64cd\u4f5c\u6d41\u7a0b<\/h4>\n
    • \u5728\u6587\u672c\u6846\u4e2d\u8f93\u5165\u4efb\u610f\u4e2d\u6587\u5185\u5bb9（\u652f\u6301\u6362\u884c\u548c\u6807\u70b9）<\/li>\n
    • \u70b9\u51fb \u201c\u5f00\u59cb\u5408\u6210\u8bed\u97f3\u201d<\/li>\n
    • \u7b49\u5f85 1~3 \u79d2，\u9875\u9762\u81ea\u52a8\u64ad\u653e\u751f\u6210\u7684 .wav \u97f3\u9891<\/li>\n
    • \u53ef\u70b9\u51fb\u4e0b\u8f7d\u6309\u94ae\u4fdd\u5b58\u672c\u5730\u4f7f\u7528<\/li>\n

      4. API \u8c03\u7528\u793a\u4f8b（Python）<\/h4>\n

      import requests<\/p>\n

      response = requests.post(
      \n "http:\/\/your-server-ip:8080\/tts",
      \n json={"text": "\u4f60\u597d，\u8fd9\u662f\u901a\u8fc7 API \u8c03\u7528\u7684\u8bed\u97f3\u5408\u6210"}
      \n)<\/p>\n

      if response.status_code == 200:
      \n data = response.json()
      \n print("Audio URL:", data['audio_url'])
      \n # \u53ef\u76f4\u63a5\u5d4c\u5165\u7f51\u9875\u64ad\u653e\u6216\u4e0b\u8f7d
      \nelse:
      \n print("Error:", response.json())<\/p>\n

      \n

      \u2705 \u603b\u7ed3：\u4f4e\u6210\u672c\u8bed\u97f3\u65b9\u6848\u7684\u6838\u5fc3\u4ef7\u503c<\/h3>\n

      \u672c\u6b21\u5b9e\u8df5\u9a8c\u8bc1\u4e86\u57fa\u4e8e ModelScope Sambert-Hifigan \u7684\u4e2d\u6587\u591a\u60c5\u611f\u8bed\u97f3\u5408\u6210\u7cfb\u7edf，\u5728\u7eaf CPU \u73af\u5883\u4e0b\u5177\u5907\u51fa\u8272\u7684\u7a33\u5b9a\u6027\u4e0e\u6027\u4ef7\u6bd4\u3002\u5176\u6838\u5fc3\u4f18\u52bf\u4f53\u73b0\u5728：<\/p>\n

      📌 \u4e09\u5927\u6838\u5fc3\u4eae\u70b9\u603b\u7ed3： 1. \u96f6 GPU \u6210\u672c：\u5168\u7a0b CPU \u63a8\u7406，\u5355\u53f0 4 \u6838\u670d\u52a1\u5668\u5373\u53ef\u652f\u6491\u5343\u6b21\u7ea7\u65e5\u8c03\u7528 2. \u5f00\u7bb1\u5373\u7528：\u5df2\u4fee\u590d\u6240\u6709\u5173\u952e\u4f9d\u8d56\u51b2\u7a81，\u675c\u7edd\u201c\u73af\u5883\u707e\u96be\u201d 3. \u53cc\u6a21\u8bbf\u95ee：\u540c\u65f6\u652f\u6301 WebUI \u4ea4\u4e92\u4e0e\u6807\u51c6\u5316 API \u96c6\u6210，\u7075\u6d3b\u9002\u914d\u5404\u7c7b\u573a\u666f<\/p>\n

      📈 \u9002\u7528\u573a\u666f\u63a8\u8350<\/h4>\n
        \n
      • \u4f01\u4e1a\u5185\u90e8\u77e5\u8bc6\u5e93\u8bed\u97f3\u64ad\u62a5<\/li>\n
      • \u6559\u80b2\u7c7b App \u7684\u8bfe\u6587\u6717\u8bfb\u529f\u80fd<\/li>\n
      • \u667a\u80fd\u786c\u4ef6\u8bbe\u5907\u7684\u79bb\u7ebf TTS \u6a21\u5757<\/li>\n
      • \u5ba2\u670d\u673a\u5668\u4eba\u5e94\u7b54\u8bed\u97f3\u751f\u6210<\/li>\n<\/ul>\n

        🔄 \u540e\u7eed\u4f18\u5316\u65b9\u5411<\/h4>\n
          \n
        • \u589e\u52a0\u60c5\u611f\u53c2\u6570 API \u63a7\u5236\u63a5\u53e3<\/li>\n
        • \u5f15\u5165\u8bed\u97f3\u514b\u9686（Voice Cloning）\u80fd\u529b<\/li>\n
        • \u652f\u6301\u6279\u91cf\u5f02\u6b65\u5408\u6210\u4efb\u52a1\u961f\u5217<\/li>\n
        • \u6dfb\u52a0 JWT \u8ba4\u8bc1\u9632\u6b62\u6ee5\u7528<\/li>\n<\/ul>\n
          \n

          📚 \u9644\u5f55：\u8d44\u6e90\u94fe\u63a5<\/h3>\n
            \n
          • ModelScope \u6a21\u578b\u4e3b\u9875：https:\/\/modelscope.cn\/models\/damo\/speech_sambert-hifigan_tts_zh-cn_16k<\/li>\n
          • GitHub \u793a\u4f8b\u4ee3\u7801\u4ed3\u5e93：https:\/\/github.com\/your-repo\/tts-flask-demo<\/li>\n
          • Docker \u955c\u50cf\u6784\u5efa\u811a\u672c（Dockerfile）\u53ef\u8054\u7cfb\u4f5c\u8005\u83b7\u53d6<\/li>\n<\/ul>\n

            \u672c\u6587\u65b9\u6848\u5df2\u5728\u591a\u4e2a\u5b9e\u9645\u9879\u76ee\u4e2d\u843d\u5730\u9a8c\u8bc1，\u771f\u6b63\u5b9e\u73b0\u4e86\u201c\u4f4e\u6210\u672c\u3001\u9ad8\u8d28\u91cf\u3001\u6613\u7ef4\u62a4\u201d\u7684\u8bed\u97f3\u5408\u6210\u670d\u52a1\u95ed\u73af\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

            \u4f4e\u6210\u672c\u8bed\u97f3\u65b9\u6848\u9a8c\u8bc1：\u5355\u53f0\u670d\u52a1\u5668\u652f\u6491\u5343\u6b21\u8c03\u7528
            \n📌 \u80cc\u666f\u4e0e\u6311\u6218：\u4e2d\u6587\u591a\u60c5\u611f\u8bed\u97f3\u5408\u6210\u7684\u843d\u5730\u9700\u6c42
            \n\u5728\u667a\u80fd\u5ba2\u670d\u3001\u6709\u58f0\u9605\u8bfb\u3001\u865a\u62df\u4e3b\u64ad\u7b49\u573a\u666f\u4e2d，\u9ad8\u8d28\u91cf\u4e2d\u6587\u8bed\u97f3\u5408\u6210（TTS） \u5df2\u6210\u4e3a\u4e0d\u53ef\u6216\u7f3a\u7684\u6280\u672f\u80fd\u529b\u3002\u4f20\u7edf\u5546\u4e1a TTS \u670d\u52a1\u867d\u7a33\u5b9a，\u4f46\u957f\u671f\u8c03\u7528\u6210\u672c\u9ad8，\u4e14\u6570\u636e\u9690\u79c1\u96be\u4ee5\u638c\u63a7\u3002\u56e0\u6b64，\u8d8a\u6765\u8d8a\u591a\u4f01\u4e1a\u5f00\u59cb\u63a2\u7d22\u81ea\u5efa\u4f4e\u6210\u672c\u3001\u53ef\u5b9a\u5236\u7684\u8bed\u97f3\u5408\u6210\u7cfb\u7edf\u3002
            \n\u7136\u800c，\u81ea\u7814 TT<\/p>\n","protected":false},"author":2,"featured_media":61699,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"topic":[],"class_list":["post-61700","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server"],"yoast_head":"\n\u4f4e\u6210\u672c\u8bed\u97f3\u65b9\u6848\u9a8c\u8bc1\uff1a\u5355\u53f0\u670d\u52a1\u5668\u652f\u6491\u5343\u6b21\u8c03\u7528 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/61700.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u4f4e\u6210\u672c\u8bed\u97f3\u65b9\u6848\u9a8c\u8bc1\uff1a\u5355\u53f0\u670d\u52a1\u5668\u652f\u6491\u5343\u6b21\u8c03\u7528 - 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