SoundGame Dev
cc0f8c008d
- 新增 web/ 纯音频 HTML5 平台：共享引擎（手势/WebAudio 三层/设置/震动）、 Node 零依赖服务器（静态 + 注册登录 + 进度存档 API） - 游戏：剑与声(RPG 新作)、声命线、暗室(重设计)、音序回响(重设计)、 节拍行者(跟随领奏重构)、盲航(同向闪避重构)；声东击西删除 - 全局功能：男声/女声双套 TTS 资产、三档语速、BGM 音量三档、 震动反馈语言(10 种震型)、服务器进度同步 - 资产：899 ogg + 899 m4a（Qwen3-TTS 双性别语音、Stable Audio 3 音效、 Mureka BGM 4+3 首），终检零缺失 - 文档：docs/design/ 13 篇设计审查文档、docs/audio/ 资产管线、 web/server/README.md API 文档
73 lines
2.7 KiB
Python
73 lines
2.7 KiB
Python
"""web/simon 语音批量生成（Qwen3-TTS CustomVoice，Serena 音色）。
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生成后写入 audio/voice/wav_tmp/*.wav，由 shell 统一 ffmpeg 转 ogg/m4a。
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每条断言：时长 > 0.3s（不足时尾部补静音到 0.35s）、峰值 > 0.05（统一峰值归一 0.8）。
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"""
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import os
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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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OUT = os.path.join(os.path.dirname(__file__), "..", "audio", "voice", "wav_tmp")
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os.makedirs(OUT, exist_ok=True)
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LINES = {
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# 开场 + 教学
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"intro": "欢迎来到音序回响。我会用六种声音演奏一段序列，请你记住顺序，再用同样的手势复现出来。先来认识这六种声音。",
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"teach_up": "向上滑，是上行琶音。",
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"teach_down": "向下滑，是低沉的下行音。",
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"teach_left": "向左滑，声音在你的左边。",
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"teach_right": "向右滑，声音在你的右边。",
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"teach_tap": "单击，是短促的鼓点。",
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"teach_doubletap": "双击，是两声连响。",
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"teach_end": "好了，记住这些声音。序列会越来越长，看你能坚持几轮。",
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# 流程提示
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"listen": "听好了。",
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"your_turn": "轮到你了。",
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# 反馈
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"correct": "答对了！",
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"wrong": "错了。",
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"new_record": "新纪录！",
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"gameover": "游戏结束。",
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"replay": "单击屏幕，再来一局。",
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# 播报拼接片段
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"score_pre": "你坚持了",
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"best_pre": "历史最高纪录，",
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"di": "第",
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"lun": "轮",
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"num_shi": "十",
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"num_0": "零", "num_1": "一", "num_2": "二", "num_3": "三", "num_4": "四",
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"num_5": "五", "num_6": "六", "num_7": "七", "num_8": "八", "num_9": "九",
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}
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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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names = list(LINES.keys())
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texts = [LINES[n] for n in names]
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wavs, sr = model.generate_custom_voice(
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text=texts,
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language=["Chinese"] * len(names),
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speaker="Serena",
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instruct="用清晰、沉稳而有引导感的声音，语速适中，像一个耐心的游戏主持人",
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)
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for name, wav in zip(names, wavs):
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wav = np.asarray(wav, dtype=np.float32)
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peak = np.max(np.abs(wav))
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assert peak > 0.05, f"{name} 峰值过小: {peak}"
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wav = wav / peak * 0.8
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dur = len(wav) / sr
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if dur < 0.35: # 单字片段补静音，保证可听清且满足时长断言
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wav = np.concatenate([wav, np.zeros(int((0.35 - dur) * sr), dtype=np.float32)])
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dur = len(wav) / sr
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assert dur > 0.3, f"{name} 时长过短: {dur}"
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path = os.path.join(OUT, name + ".wav")
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sf.write(path, wav, sr)
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print(f"{name}: {dur:.2f}s peak={np.max(np.abs(wav)):.2f}")
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print("done", len(names), "clips")
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