185 lines
6.8 KiB
Python
185 lines
6.8 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""R6 缺口语音生成（docs/design/11-rpg-battle-rebalance.md §6）：tut_b0 / tut_b6 /
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btl_flee_fail / boss1_warn 四句，双性别（male=Uncle_Fu / female=Serena），
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instruct 沿用 tools/gen_voice_dual.py 的 rpg 旁白常量。
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用法（GPU 串行）：
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source env.d/tts.sh
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flock .gpu.lock .venv-tts/bin/python web/rpg/gen/gen_gap_voice.py # 生成 staging wav
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.venv-tts/bin/python web/rpg/gen/gen_gap_voice.py --convert # 转 ogg+m4a 落盘
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.venv-tts/bin/python web/rpg/gen/gen_gap_voice.py --check # 两性时长离群检查
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staging: web/rpg/gen/staging/voice/<gender>/<id>.wav（断点续跑，删 wav 即重录该句）
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落盘: web/rpg/audio/voice/<gender>/<id>.{ogg,m4a}
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质量控制同主管线：时长 >0.3s、峰值 >0.05、峰值归一 0.89、>40 字拆句拼接（句间 0.12s）。
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"""
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import argparse
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import os
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import subprocess
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import sys
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os.environ.setdefault("HF_HOME", "/home/xsl/SoundGame/models/hf")
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os.environ.setdefault("HF_ENDPOINT", "https://hf-mirror.com")
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ROOT = "/home/xsl/SoundGame"
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sys.path.insert(0, os.path.join(ROOT, "tools"))
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from gen_voice_dual import split_text, valid_wav, PEAK_NORM, GAP_SEC # noqa: E402 只读复用主管线
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GAME = "rpg"
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STAGING = os.path.join(ROOT, "web", "rpg", "gen", "staging", "voice")
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OUT = os.path.join(ROOT, "web", GAME, "audio", "voice")
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FFMPEG = os.path.join(ROOT, "tools", "bin", "ffmpeg")
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SPEAKERS = {"male": "Uncle_Fu", "female": "Serena"}
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INSTRUCT = {
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"male": "低沉醇厚的男声，像说书人，平静有韵味",
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"female": "平静清晰的年轻女声，像在讲武侠故事",
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}
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# 台词全文照录 11 号文档 §6
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LINES = [
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("tut_b0", "战斗里，左右滑选招式，单击出手。听到这个声音，就是你的回合。先滑一滑，试试。"),
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("tut_b6", "来不及格挡，就选防御。左右滑，选防御，单击。"),
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("btl_flee_fail", "没甩掉！它追上来了。"),
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("boss1_warn", "里面就是黑风寨主。你现在回去练练再来，也来得及。"),
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]
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def staging_path(gender, fid):
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return os.path.join(STAGING, gender, fid + ".wav")
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def generate():
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import numpy as np
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import soundfile as sf
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import torch
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from qwen_tts import Qwen3TTSModel
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model = Qwen3TTSModel.from_pretrained(
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"Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice",
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device_map="cuda:0",
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dtype=torch.bfloat16,
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)
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print("model loaded", flush=True)
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for gender in ("male", "female"):
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speaker = SPEAKERS[gender]
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instruct = INSTRUCT[gender]
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os.makedirs(os.path.join(STAGING, gender), exist_ok=True)
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# 展开成 (fid, chunk_idx, text)，跳过已完成
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items = []
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for fid, text in LINES:
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if valid_wav(staging_path(gender, fid)):
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continue
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for ci, ctext in enumerate(split_text(text)):
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items.append((fid, ci, ctext))
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if not items:
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print(f"[{gender}] nothing to do", flush=True)
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continue
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results = {}
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for i in range(0, len(items), 6):
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batch = items[i:i + 6]
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wavs, sr = model.generate_custom_voice(
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text=[b[2] for b in batch],
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language=["Chinese"] * len(batch),
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speaker=[speaker] * len(batch),
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instruct=[instruct] * len(batch),
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max_new_tokens=2048,
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)
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for (fid, ci, _t), wav in zip(batch, wavs):
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results.setdefault(fid, {})[ci] = np.asarray(wav, dtype=np.float32)
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print(f"[{gender}] batch {i // 6 + 1} (n={len(batch)})", flush=True)
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gap = np.zeros(int(GAP_SEC * sr), dtype=np.float32)
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for fid, text in LINES:
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path = staging_path(gender, fid)
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if valid_wav(path):
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continue
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got = results.get(fid, {})
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n_chunks = len(split_text(text))
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assert len(got) == n_chunks, f"{gender}/{fid}: 缺 chunk {len(got)}/{n_chunks}"
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wav = got[0]
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for ci in range(1, n_chunks):
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wav = np.concatenate([wav, gap, got[ci]])
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peak = float(np.max(np.abs(wav)))
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assert peak > 0.05, f"{gender}/{fid}: peak {peak:.3f}"
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wav = wav / peak * PEAK_NORM
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dur = len(wav) / sr
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assert dur > 0.3, f"{gender}/{fid}: dur {dur:.2f}s"
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sf.write(path, wav, sr)
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print(f"[ok] {gender}/{fid} {dur:.2f}s chunks={n_chunks}", flush=True)
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def check():
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import numpy as np
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import soundfile as sf
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problems = []
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for fid, _text in LINES:
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durs = {}
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for gender in ("male", "female"):
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path = staging_path(gender, fid)
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if not os.path.exists(path):
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durs[gender] = None
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continue
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data, sr = sf.read(path)
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peak = float(np.max(np.abs(data)))
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durs[gender] = len(data) / sr
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if durs[gender] <= 0.3 or peak <= 0.05:
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problems.append(f"{gender}/{fid}: 质量不达标 dur={durs[gender]:.2f} peak={peak:.3f}")
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m, f = durs["male"], durs["female"]
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if m is None or f is None:
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problems.append(f"{fid}: 缺 {'male' if m is None else 'female'}")
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continue
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ratio = max(m, f) / min(m, f)
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flag = " <-- OUTLIER" if ratio > 3 else ""
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if ratio > 3:
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problems.append(f"{fid}: 时长离群 m={m:.2f}s f={f:.2f}s ratio={ratio:.1f}")
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print(f" {fid:16s} m={m:6.2f}s f={f:6.2f}s{flag}")
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if problems:
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print("PROBLEMS:")
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for p in problems:
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print(" ", p)
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return 1
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print("ALL OK")
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return 0
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def convert():
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total = 0
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for gender in ("male", "female"):
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dst_dir = os.path.join(OUT, gender)
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os.makedirs(dst_dir, exist_ok=True)
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for fid, _text in LINES:
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src = staging_path(gender, fid)
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if not os.path.exists(src):
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print(f"[convert] WARN missing {gender}/{fid}.wav")
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continue
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base = os.path.join(dst_dir, fid)
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subprocess.run([FFMPEG, "-y", "-v", "error", "-i", src,
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"-ar", "44100", "-c:a", "libvorbis", "-q:a", "3", base + ".ogg"], check=True)
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subprocess.run([FFMPEG, "-y", "-v", "error", "-i", src,
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"-ar", "44100", "-c:a", "aac", "-b:a", "128k", base + ".m4a"], check=True)
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total += 1
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print(f"converted {total} files (ogg+m4a each)")
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--check", action="store_true")
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ap.add_argument("--convert", action="store_true")
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args = ap.parse_args()
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if args.check:
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sys.exit(check())
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if args.convert:
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convert()
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return
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generate()
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if __name__ == "__main__":
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main()
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