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High-quality local text-to-speech using Kokoro TTS engine. Zero API cost, fully offline.
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| name | kokoro-tts |
| description | High-quality local text-to-speech using Kokoro TTS engine. Zero API cost, fully offline. |
| metadata | {"xiaodazi":{"dependency_level":"external","os":["common"],"backend_type":"local","user_facing":true}} |
| capabilities | ["tts","speech_synthesis"] |
使用 Kokoro TTS 引擎在本地生成高质量语音，零 API 成本，完全离线。
pip install kokoro-onnx soundfile
首次使用需下载模型文件（约 300MB）。
from kokoro_onnx import Kokoro
kokoro = Kokoro("kokoro-v1.0.onnx", "voices-v1.0.bin")
samples, sample_rate = kokoro.create(
"你好，这是一段测试语音。",
voice="af_heart",
speed=1.0,
lang="z", # z=中文, e=英文
)
import soundfile as sf
sf.write("output.wav", samples, sample_rate)
| Voice ID | 性别 | 语言 | 风格 |
|---|---|---|---|
af_heart | 女 | 中/英 | 温暖自然 |
af_bella | 女 | 中/英 | 清晰专业 |
am_adam | 男 | 中/英 | 沉稳 |
am_michael | 男 | 中/英 | 活力 |
长文本自动按句分段合成，避免内存溢出：
import re
sentences = re.split(r'[。！？\.\!\?]', long_text)
all_samples = []
for s in sentences:
if s.strip():
samples, sr = kokoro.create(s.strip() + "。", voice="af_heart", lang="z")
all_samples.append(samples)
import numpy as np
combined = np.concatenate(all_samples)
sf.write("output.wav", combined, sr)