voiceover

# 配音生成技能 ## 技术选型 | 方案 | 优点 | 缺点 | |------|------|------| | edge-tts | 免费、音质好、多语言支持 | 需要网络 | | Azure TTS | 更多声音选择、更稳定 | 需要付费 | **推荐**: edge-tts ## 声音选择 ### 中文声音列表 (zh-CN) | 声音 ID | 性别 | 风格 | 适用场景 | |---------|------|------|----------| | zh-CN-XiaoxiaoNeural | 女 | 温暖亲切 | 产品介绍、教程 | | zh-CN-YunxiNeural | 男 | 专业稳重 | 企业宣传、正式场合 | | zh-CN-YunjianNeural | 男 | 激情活力 | 科技发布、激励视频 | | zh-CN-XiaoyiNeural | 女 | 年轻活泼 | 创意内容、轻松主题 | | zh-CN-YunyangNeural | 男 | 新闻播报 | 资讯类、严肃主题 | ### 英文声音列表 (en-US) | 声音 ID | 性别 | 风格 | 适用场景 | |---------|------|------|----------| | en-US-GuyNeural | 男 | 专业稳重 | 企业宣传、产品介绍 | | en-US-JennyNeural | 女 | 温暖友好 | 教程、客户服务 | | en-US-AriaNeural | 女 | 清晰专业 | 新闻、正式场合 | | en-US-DavisNeural | 男 | 年轻活力 | 科技内容、创意视频 | | en-US-JasonNeural | 男 | 激情活力 | 发布会、激励视频 | | en-US-SaraNeural | 女 | 年轻活泼 | 社交媒体、轻松主题 | ### 声音选择建议 **中文视频:** | 视频类型 | 推荐声音 | |----------|----------| | 产品演示 | XiaoxiaoNeural (女) | | 公司介绍 | YunxiNeural (男) 或 XiaoxiaoNeural | | 科技历程 | **YunjianNeural (男)** - 有激情感 | | 教程类 | XiaoxiaoNeural (女) | | 发布会风格 | YunjianNeural (男) | **英文视频:** | 视频类型 | 推荐声音 | |----------|----------| | 产品演示 | GuyNeural (男) 或 JennyNeural (女) | | 公司介绍 | GuyNeural (男) 或 AriaNeural (女) | | 科技历程 | **JasonNeural (男)** - 有激情感 | | 教程类 | JennyNeural (女) | | 发布会风格 | JasonNeural (男) 或 DavisNeural (男) | ## 时间线计算 ### 核心公式 ```python # 最终视频时间 = 录屏事件时间 + 偏移量 DEMO_START = OPENING_DURATION + FEATURES_DURATION final_time = recording_time + DEMO_START ``` ### 图文视频时间线 对于图文展示型视频，时间线由分镜直接定义： ```python # 场景时间配置 SCENES = { "opening": {"start": 0, "duration": 8}, "scene_1": {"start": 8, "duration": 14}, "scene_2": {"start": 22, "duration": 16}, # ... } # 配音定义 - 直接基于场景时间 VOICEOVER_SEGMENTS = [ (0.5, 7.5, "片头配音..."), # 场景 opening 内 (8.5, 21.5, "场景1配音..."), # 场景 scene_1 内 (22.5, 37.5, "场景2配音..."), # 场景 scene_2 内 ] ``` ## 配音验证机制 (重要) ### 自动化验证函数 ```python def validate_voiceover(segments, total_duration): """ 验证配音时间线 返回: (是否通过, 问题列表) """ issues = [] for i, seg in enumerate(segments): # 检查1: 配音是否超出场景时长 actual_end = seg["start_time"] + seg["actual_duration"] if seg["actual_duration"] > seg["target_duration"] + 0.5: issues.append({ "type": "duration_exceeded", "segment": i, "message": f"片段{i}: 实际({seg['actual_duration']:.1f}s) > 目标({seg['target_duration']:.1f}s)", "severity": "warning" }) # 检查2: 配音是否与下一段重叠 if i < len(segments) - 1: next_start = segments[i+1]["start_time"] if actual_end > next_start: issues.append({ "type": "overlap", "segment": i, "message": f"片段{i}和{i+1}重叠: {actual_end:.1f}s > {next_start:.1f}s", "severity": "error" }) # 检查3: 最后一段是否超出视频时长 last_seg = segments[-1] last_end = last_seg["start_time"] + last_seg["actual_duration"] if last_end > total_duration + 1: issues.append({ "type": "exceeds_video", "message": f"配音结束({last_end:.1f}s) > 视频时长({total_duration}s)", "severity": "error" }) # 检查4: 空白间隙 for i in range(len(segments) - 1): current_end = segments[i]["start_time"] + segments[i]["actual_duration"] next_start = segments[i+1]["start_time"] gap = next_start - current_end if gap > 3: issues.append({ "type": "large_gap", "segment": i, "message": f"片段{i}和{i+1}之间有{gap:.1f}s空白", "severity": "warning" }) passed = not any(issue["severity"] == "error" for issue in issues) return passed, issues ``` ### 验证报告输出 ```python def print_validation_report(segments, total_duration): """打印配音验证报告""" passed, issues = validate_voiceover(segments, total_duration) print("╔" + "═" * 58 + "╗") print("║" + "配音验证报告".center(54) + "║") print("╠" + "═" * 58 + "╣") print("║ 片段 │ 开始 │ 目标时长 │ 实际时长 │ 状态 ║") print("╠" + "═" * 58 + "╣") for i, seg in enumerate(segments): status = "✅ OK" if seg["actual_duration"] <= seg["target_duration"] + 0.5 else "⚠️ 超时" print(f"║ {i:2d} │ {seg['start_time']:5.1f}s │ {seg['target_duration']:5.1f}s │ {seg['actual_duration']:5.1f}s │ {status:10s} ║") print("╠" + "═" * 58 + "╣") if passed: print("║ ✅ 验证通过 ║") else: print("║ ❌ 验证失败，请检查以下问题: ║") for issue in issues: if issue["severity"] == "error": print(f"║ ❌ {issue['message'][:50]:50s} ║") print("╚" + "═" * 58 + "╝") return passed ``` ## 完整配音脚本模板 (V2 - 多语言版) ```python #!/usr/bin/env python3 """ 配音生成脚本 V2 - 包含验证机制 + 多语言支持 """ import asyncio import subprocess from pathlib import Path import json import re # ========== 配置 ========== LANGUAGE = "zh" # "zh" 或 "en" VOICE = "zh-CN-YunjianNeural" # 科技感男声 # 英文示例: VOICE = "en-US-JasonNeural" OUTPUT_DIR = Path("public/audio") TOTAL_DURATION = 85 # 视频总时长 # 配音段落定义 (开始时间, 结束时间, 配音文字) VOICEOVER_SEGMENTS = [ (0.5, 7.5, "配音内容1"), (8.5, 21.5, "配音内容2"), # ... ] # ========== 工具函数 ========== def get_audio_duration(file_path): """获取音频时长""" result = subprocess.run( ["ffprobe", "-v", "error", "-show_entries", "format=duration", "-of", "default=noprint_wrappers=1:nokey=1", str(file_path)], capture_output=True, text=True ) return float(result.stdout.strip()) def validate_voiceover(segments, total_duration): """验证配音时间线""" issues = [] for i, seg in enumerate(segments): # 检查时长 if seg["actual_duration"] > seg["target_duration"] + 0.5: issues.append(f"⚠️ 片段{i}: 超时 {seg['actual_duration'] - seg['target_duration']:.1f}s") # 检查重叠 if i < len(segments) - 1: actual_end = seg["start_time"] + seg["actual_duration"] next_start = segments[i+1]["start_time"] if actual_end > next_start: issues.append(f"❌ 片段{i}和{i+1}重叠") return len([i for i in issues if i.startswith("❌")]) == 0, issues # ========== 多语言支持函数 ========== def calculate_natural_duration(text, language): """计算文本自然朗读时长""" if language == "zh": # 中文: 约 4 字/秒 char_count = len(re.sub(r'[^\u4e00-\u9fff]', '', text)) return char_count / 4.0 else: # 英文: 约 150 词/分钟 = 2.5 词/秒 word_count = len(text.split()) return word_count / 2.5 # ========== 生成函数 ========== async def generate_segment(index, start, end, text): """生成单个配音片段（支持多语言）""" import edge_tts output_file = OUTPUT_DIR / f"vo_{index:02d}.mp3" duration_target = end - start # 计算语速（多语言支持） natural_duration = calculate_natural_duration(text, LANGUAGE) if natural_duration > duration_target: rate_adjust = min(35, int((natural_duration / duration_target - 1) * 100)) rate = f"+{rate_adjust}%" elif natural_duration < duration_target * 0.7: rate_adjust = min(15, int((1 - natural_duration / duration_target) * 50)) rate = f"-{rate_adjust}%" else: rate = "+0%" # 生成配音 communicate = edge_tts.Communicate(text=text, voice=VOICE, rate=rate) await communicate.save(str(output_file)) actual_duration = get_audio_duration(output_file) return { "index": index, "file": output_file.name, "start_time": start, "target_duration": duration_target, "actual_duration": actual_duration, "text": text[:20] + "...", "rate": rate, "language": LANGUAGE, } def merge_audio(segments): """合并音频""" filter_parts = [] inputs = [] for i, seg in enumerate(segments): inputs.extend(["-i", str(OUTPUT_DIR / seg["file"])]) delay_ms = int(seg["start_time"] * 1000) filter_parts.append(f"[{i}:a]adelay={delay_ms}|{delay_ms}[a{i}];") mix_inputs = "".join([f"[a{i}]" for i in range(len(segments))]) filter_parts.append(f"{mix_inputs}amix=inputs={len(segments)}:duration=longest[out]") output_file = OUTPUT_DIR / "synced_voiceover.mp3" subprocess.run([