147 lines
4.8 KiB
Python
147 lines
4.8 KiB
Python
#!/usr/bin/env python3
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"""
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generate_audio.py — 用 OpenAI TTS 把 english_units.html 裡所有英文句子跑成 mp3。
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用法：
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export OPENAI_API_KEY=你的key
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python3 generate_audio.py [--force] [--voice shimmer] [--speed 0.9]
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不需要任何套件（純 Python 標準函式庫），不需要 ffmpeg（OpenAI 直接回 mp3）。
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聲音：alloy / ash / ballad / coral / echo / fable / nova / onyx / sage / shimmer / verse
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模型：gpt-4o-mini-tts（預設，支援 instructions）/ tts-1-hd / tts-1
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"""
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import argparse
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import hashlib
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import json
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import os
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import re
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import sys
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import time
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import urllib.error
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import urllib.request
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent
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HTML = ROOT / "english_units.html"
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AUDIO_DIR = ROOT / "audio"
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OPENAI_TTS_URL = "https://api.openai.com/v1/audio/speech"
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INSTRUCTIONS = (
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"Speak in a warm, playful, encouraging tone like a cheerful older sister reading a "
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"picture book to a young child. Clear American English, slightly slower than normal, "
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"full of warmth and excitement. Sound friendly and approachable, not stiff. "
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"Pronounce every word clearly."
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)
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def extract_texts(html_text: str):
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pattern = re.compile(r'en:\s*"((?:[^"\\]|\\.)*)"')
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clean, seen = [], set()
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for m in pattern.findall(html_text):
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t = m.replace('\\"', '"').replace("\\'", "'")
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t = re.sub(r'<[^>]+>', '', t).strip()
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if t and t not in seen:
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seen.add(t)
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clean.append(t)
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return clean
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def hash_text(text: str) -> str:
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return hashlib.sha1(text.encode('utf-8')).hexdigest()[:16]
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def tts(api_key: str, text: str, voice: str, model: str,
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fmt: str = 'mp3', speed: float = 0.9) -> bytes:
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payload = {
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"model": model,
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"input": text,
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"voice": voice,
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"response_format": fmt,
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"speed": speed,
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}
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if model.startswith("gpt-4o"):
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payload["instructions"] = INSTRUCTIONS
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req = urllib.request.Request(
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OPENAI_TTS_URL,
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data=json.dumps(payload).encode('utf-8'),
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headers={
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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},
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)
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with urllib.request.urlopen(req, timeout=90) as r:
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return r.read()
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument('--force', action='store_true', help='重新產生已存在的檔案')
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ap.add_argument('--voice', default='nova',
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help='alloy/ash/ballad/coral/echo/fable/nova/onyx/sage/shimmer/verse')
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ap.add_argument('--speed', type=float, default=0.92,
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help='0.25–4.0，<1 變慢（預設 0.92）')
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ap.add_argument('--model', default='gpt-4o-mini-tts',
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choices=['gpt-4o-mini-tts', 'tts-1-hd', 'tts-1'])
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ap.add_argument('--format', default='mp3',
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choices=['mp3', 'opus', 'aac', 'flac', 'wav', 'pcm'])
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ap.add_argument('--sleep', type=float, default=0.2)
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args = ap.parse_args()
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api_key = os.getenv('OPENAI_API_KEY')
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if not api_key:
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print('需要 OPENAI_API_KEY', file=sys.stderr)
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print(' 去 https://platform.openai.com/api-keys 拿', file=sys.stderr)
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sys.exit(1)
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AUDIO_DIR.mkdir(exist_ok=True)
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texts = extract_texts(HTML.read_text(encoding='utf-8'))
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print(f'找到 {len(texts)} 句不重複英文')
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print(f'模型 {args.model} 聲音 {args.voice} 速度 {args.speed}x 格式 {args.format}')
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print()
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manifest = {}
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made = skipped = failed = 0
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for i, text in enumerate(texts, 1):
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h = hash_text(text)
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out = AUDIO_DIR / f'{h}.{args.format}'
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label = text if len(text) <= 55 else text[:52] + '...'
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if out.exists() and not args.force:
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manifest[text] = out.name
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skipped += 1
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print(f'[{i:3}/{len(texts)}] skip {label}')
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continue
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print(f'[{i:3}/{len(texts)}] gen {label}')
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try:
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audio = tts(api_key, text, args.voice, args.model, args.format, args.speed)
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out.write_bytes(audio)
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manifest[text] = out.name
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made += 1
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except urllib.error.HTTPError as e:
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failed += 1
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body = e.read().decode('utf-8', errors='ignore')[:240]
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print(f' HTTP {e.code}: {body}')
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except Exception as e:
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failed += 1
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print(f' FAIL: {e}')
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time.sleep(args.sleep)
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(AUDIO_DIR / 'manifest.json').write_text(
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json.dumps(manifest, ensure_ascii=False, indent=2), encoding='utf-8')
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(AUDIO_DIR / 'manifest.js').write_text(
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'window.__audioManifest = ' + json.dumps(manifest, ensure_ascii=False) + ';\n',
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encoding='utf-8',
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)
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print()
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print(f'完成：新產生 {made}、跳過 {skipped}、失敗 {failed}')
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print(f'檔案在 {AUDIO_DIR}/')
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if __name__ == '__main__':
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main()
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