346 lines
11 KiB
JavaScript
346 lines
11 KiB
JavaScript
/**
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* 光湖视频AI系统 · 音频分轨引擎
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* D140 · 铸渊 ICE-GL-ZY001 · 2026-06-23
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*
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* 将混合音频分离为三轨: 对白(voice) / 背景音乐(bgm) / 音效(sfx)
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* 基于 FFmpeg 音频滤波链 + 频率/动态范围分析
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*
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* 工作原理:
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* 1. 对白轨: 人声频率范围(80Hz-8kHz)带通 + 动态范围压缩
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* 2. BGM轨: 低频段(20-250Hz) + 高频段(8kHz+)的中低能量部分
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* 3. SFX轨: 高频瞬态(打击类) + 非人声中频
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*
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* 输出三轨独立WAV，供 video-editor.js 混音使用
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*
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* 使用方式:
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* const { splitAudioStems, analyzeAudioLevels } = require('./audio-stem-splitter');
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* const stems = await splitAudioStems('input.mp4', './stems/');
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* // stems.voice, stems.bgm, stems.sfx → 独立WAV文件路径
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*
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* 铸渊 ICE-GL-ZY001 · D140
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*/
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const { execSync } = require('child_process');
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const fs = require('fs');
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const path = require('path');
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// ==================== 核心分轨 ====================
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/**
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* 将音视频文件分离为三轨: 对白 / BGM / 音效
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*
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* @param {string} inputPath - 输入文件（视频或音频）
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* @param {string} outputDir - 输出目录
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* @param {object} [opts]
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* @param {number} [opts.voiceLow=80] - 人声低频截止 Hz
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* @param {number} [opts.voiceHigh=8000] - 人声高频截止 Hz
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* @param {number} [opts.bgmLow=20] - BGM低频 Hz
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* @param {number} [opts.bgmHigh=250] - BGM低频截止 Hz
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* @param {number} [opts.sfxThreshold] - SFX瞬态检测阈值(dB)
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* @returns {Promise<{voice: string, bgm: string, sfx: string, raw: string, meta: object}>}
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*/
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async function splitAudioStems(inputPath, outputDir, opts = {}) {
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if (!fs.existsSync(inputPath)) {
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throw new Error(`输入文件不存在: ${inputPath}`);
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}
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// 确保输出目录
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if (!fs.existsSync(outputDir)) {
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fs.mkdirSync(outputDir, { recursive: true });
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}
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const baseName = path.basename(inputPath, path.extname(inputPath));
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const rawWav = path.join(outputDir, `${baseName}_raw.wav`);
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const voiceWav = path.join(outputDir, `${baseName}_voice.wav`);
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const bgmWav = path.join(outputDir, `${baseName}_bgm.wav`);
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const sfxWav = path.join(outputDir, `${baseName}_sfx.wav`);
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const metaJson = path.join(outputDir, `${baseName}_stems_meta.json`);
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console.log(`[StemSplitter] 输入: ${path.basename(inputPath)}`);
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console.log(`[StemSplitter] 输出: ${outputDir}`);
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// Step 1: 提取原始音频
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console.log('[StemSplitter] 1/4 提取原始音频...');
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execSync(
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`ffmpeg -y -i "${inputPath}" -vn -acodec pcm_s16le -ar 48000 -ac 2 "${rawWav}" 2>/dev/null`,
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{ timeout: 60000 }
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);
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if (!fs.existsSync(rawWav)) {
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throw new Error('原始音频提取失败');
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}
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const duration = probeDuration(rawWav);
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console.log(` 原始音频: ${duration.toFixed(1)}s`);
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// Step 2: 分离对白轨（人声频段带通 + 动态增强）
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console.log('[StemSplitter] 2/4 分离对白轨...');
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extractVoiceTrack(rawWav, voiceWav, opts);
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// Step 3: 分离BGM轨（低频 + 宽频带中低能量）
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console.log('[StemSplitter] 3/4 分离BGM轨...');
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extractBgmTrack(rawWav, bgmWav, opts);
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// Step 4: 分离SFX轨（高频瞬态 + 残余中频）
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console.log('[StemSplitter] 4/4 分离音效轨...');
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extractSfxTrack(rawWav, sfxWav, voiceWav, bgmWav, opts);
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// 生成元数据
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const meta = {
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input: inputPath,
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duration: duration,
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tracks: {
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voice: { file: voiceWav, duration: probeDuration(voiceWav) },
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bgm: { file: bgmWav, duration: probeDuration(bgmWav) },
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sfx: { file: sfxWav, duration: probeDuration(sfxWav) },
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},
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createdAt: new Date().toISOString(),
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};
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fs.writeFileSync(metaJson, JSON.stringify(meta, null, 2));
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console.log(`[StemSplitter] ✅ 分轨完成`);
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console.log(` 对白: ${path.basename(voiceWav)} (${meta.tracks.voice.duration.toFixed(1)}s)`);
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console.log(` BGM: ${path.basename(bgmWav)} (${meta.tracks.bgm.duration.toFixed(1)}s)`);
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console.log(` 音效: ${path.basename(sfxWav)} (${meta.tracks.sfx.duration.toFixed(1)}s)`);
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return {
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voice: voiceWav,
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bgm: bgmWav,
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sfx: sfxWav,
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raw: rawWav,
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meta,
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};
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}
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// ==================== 对白轨提取 ====================
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function extractVoiceTrack(inputWav, outputWav, opts = {}) {
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const voiceLow = opts.voiceLow || 80;
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const voiceHigh = opts.voiceHigh || 8000;
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// 滤波链:
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// 1. highpass=f=voiceLow — 去除低频噪声
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// 2. lowpass=f=voiceHigh — 限制人声高频范围
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// 3. compand — 动态范围压缩，增强人声
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// 4. afftdn=nr=10 — 降噪
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const filter = [
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`highpass=f=${voiceLow}`,
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`lowpass=f=${voiceHigh}`,
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`compand=attacks=0:points=-80/-90|-45/-15|-27/-9|0/-7|20/-7`,
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`afftdn=nr=10:nf=-25`,
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].join(',');
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execSync(
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`ffmpeg -y -i "${inputWav}" -af "${filter}" -acodec pcm_s16le -ar 48000 -ac 2 "${outputWav}" 2>/dev/null`,
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{ timeout: 120000 }
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);
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if (!fs.existsSync(outputWav)) {
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throw new Error('对白轨提取失败');
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}
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}
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// ==================== BGM轨提取 ====================
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function extractBgmTrack(inputWav, outputWav, opts = {}) {
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const bgmLow = opts.bgmLow || 20;
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const bgmHigh = opts.bgmHigh || 250;
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// BGM特征: 低频持续 + 宽频带中低能量
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// 滤波链:
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// 1. lowpass=f=bgmHigh — 截取低频段（鼓/贝斯/低频氛围）
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// 2. bass=g=3 — 增强低频
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// 3. compand — 压缩动态范围，使BGM更平稳
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// 4. volume=0.7 — 稍微降低（混音时通常BGM低于人声）
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const filter = [
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`lowpass=f=${bgmHigh}`,
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`bass=g=3:f=${bgmLow}:w=80`,
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`compand=attacks=1:decays=1:points=-80/-90|-45/-20|0/-12|20/-12`,
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`volume=0.7`,
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].join(',');
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execSync(
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`ffmpeg -y -i "${inputWav}" -af "${filter}" -acodec pcm_s16le -ar 48000 -ac 2 "${outputWav}" 2>/dev/null`,
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{ timeout: 120000 }
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);
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if (!fs.existsSync(outputWav)) {
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throw new Error('BGM轨提取失败');
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}
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}
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// ==================== SFX轨提取 ====================
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function extractSfxTrack(inputWav, outputWav, voiceWav, bgmWav, opts = {}) {
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// SFX = 原始音频 - 对白 - BGM
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// 方法: 用 sidechaincompress 或直接用频段提取
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//
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// 滤波链:
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// 1. highpass=f=2000 — 取高频段（打击/碰撞/环境音效多在高频）
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// 2. 用原始音频减去voice和bgm的频段
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// 实际实现: 取高频 + 中频瞬态部分
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const filter = [
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`highpass=f=1500`, // 高频段
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`treble=g=2:f=4000`, // 高频增强
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`compand=attacks=0:decays=0.3:points=-80/-90|-30/-30|0/-5|20/-5`, // 快速响应瞬态
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`volume=0.8`,
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`silenceremove=start_periods=0:start_threshold=-50dB:start_silence=0.1:stop_threshold=-50dB:stop_silence=0.05`,
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].join(',');
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execSync(
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`ffmpeg -y -i "${inputWav}" -af "${filter}" -acodec pcm_s16le -ar 48000 -ac 2 "${outputWav}" 2>/dev/null`,
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{ timeout: 120000 }
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);
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if (!fs.existsSync(outputWav)) {
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throw new Error('音效轨提取失败');
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}
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}
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// ==================== 音频电平分析 ====================
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/**
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* 分析音频文件的电平信息（RMS、峰值、LUFS近似值）
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* 用于自动混音决策
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*
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* @param {string} audioPath
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* @returns {{rms: number, peak: number, duration: number, channels: number}}
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*/
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function analyzeAudioLevels(audioPath) {
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if (!fs.existsSync(audioPath)) {
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throw new Error(`音频文件不存在: ${audioPath}`);
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}
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// 使用 ffprobe 获取音频信息
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const probeOut = execSync(
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`ffprobe -v quiet -show_entries format=duration:stream=channels,sample_rate -of json "${audioPath}"`,
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{ encoding: 'utf8', timeout: 5000 }
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);
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const probeData = JSON.parse(probeOut);
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const duration = parseFloat(probeData.format?.duration || 0);
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const channels = probeData.streams?.[0]?.channels || 2;
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// 使用 ffmpeg volumedetect 获取电平
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const volOut = execSync(
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`ffmpeg -i "${audioPath}" -af volumedetect -f null /dev/null 2>&1 | grep -E "mean_volume|max_volume"`,
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{ encoding: 'utf8', timeout: 30000 }
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);
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const meanMatch = volOut.match(/mean_volume:\s*(-?\d+\.?\d*)\s*dB/);
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const maxMatch = volOut.match(/max_volume:\s*(-?\d+\.?\d*)\s*dB/);
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const rms = meanMatch ? parseFloat(meanMatch[1]) : -20;
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const peak = maxMatch ? parseFloat(maxMatch[1]) : -3;
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return {
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rms, // RMS电平 (dB)
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peak, // 峰值电平 (dB)
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duration, // 时长 (秒)
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channels, // 声道数
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sampleRate: probeData.streams?.[0]?.sample_rate || 48000,
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};
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}
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// ==================== 自动混音建议 ====================
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/**
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* 根据三轨电平分析，生成混音参数建议
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*
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* @param {string} voiceWav
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* @param {string} bgmWav
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* @param {string} sfxWav
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* @returns {{voiceVolume: number, bgmVolume: number, sfxVolume: number, reasoning: string[]}}
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*/
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function suggestMixLevels(voiceWav, bgmWav, sfxWav) {
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const reasoning = [];
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// 分析各轨电平
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const voiceLevel = analyzeAudioLevels(voiceWav);
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const bgmLevel = bgmWav && fs.existsSync(bgmWav) ? analyzeAudioLevels(bgmWav) : null;
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const sfxLevel = sfxWav && fs.existsSync(sfxWav) ? analyzeAudioLevels(sfxWav) : null;
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// 目标: 对白 > BGM > SFX（一般情况）
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// 对白 RMS 目标: -16 ~ -12 dB
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// BGM RMS 目标: -24 ~ -20 dB (比对白低8dB左右)
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// SFX RMS 目标: -20 ~ -15 dB
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let voiceVolume = 1.0;
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let bgmVolume = 0.4;
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let sfxVolume = 0.6;
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// 根据对白RMS调整
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const voiceTarget = -14;
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if (voiceLevel.rms < voiceTarget - 3) {
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voiceVolume = Math.min(1.5, (voiceTarget - voiceLevel.rms) / 6 + 1.0);
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reasoning.push(`对白RMS偏低(${voiceLevel.rms}dB)，增益×${voiceVolume.toFixed(2)}`);
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} else if (voiceLevel.rms > voiceTarget + 3) {
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voiceVolume = Math.max(0.5, 1.0 - (voiceLevel.rms - voiceTarget) / 10);
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reasoning.push(`对白RMS偏高(${voiceLevel.rms}dB)，衰减×${voiceVolume.toFixed(2)}`);
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}
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// 根据BGM电平调整
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if (bgmLevel) {
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const bgmTarget = -22;
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const bgmDiff = bgmLevel.rms - bgmTarget;
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if (Math.abs(bgmDiff) > 3) {
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bgmVolume = Math.max(0.15, Math.min(0.8, 0.4 * Math.pow(10, -bgmDiff / 20)));
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reasoning.push(`BGM电平调整: RMS=${bgmLevel.rms}dB → 音量×${bgmVolume.toFixed(2)}`);
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}
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}
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// 根据SFX电平调整
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if (sfxLevel) {
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const sfxTarget = -18;
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const sfxDiff = sfxLevel.rms - sfxTarget;
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if (Math.abs(sfxDiff) > 3) {
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sfxVolume = Math.max(0.2, Math.min(1.0, 0.6 * Math.pow(10, -sfxDiff / 20)));
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reasoning.push(`SFX电平调整: RMS=${sfxLevel.rms}dB → 音量×${sfxVolume.toFixed(2)}`);
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}
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}
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// 确保对白比BGM高至少6dB
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if (bgmLevel && voiceLevel.rms + 20 * Math.log10(voiceVolume) <
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bgmLevel.rms + 20 * Math.log10(bgmVolume) + 6) {
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bgmVolume *= 0.7;
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reasoning.push(`对白-BGM间距不足6dB，BGM再降×0.7`);
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}
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return {
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voiceVolume: Math.round(voiceVolume * 100) / 100,
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bgmVolume: Math.round(bgmVolume * 100) / 100,
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sfxVolume: Math.round(sfxVolume * 100) / 100,
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voiceLevel,
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bgmLevel,
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sfxLevel,
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reasoning,
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};
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}
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// ==================== 工具函数 ====================
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function probeDuration(filePath) {
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try {
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const out = execSync(
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`ffprobe -v quiet -show_entries format=duration -of csv=p=0 "${filePath}"`,
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{ encoding: 'utf8', timeout: 5000 }
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);
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return parseFloat(out.trim()) || 0;
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} catch (_) {
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return 0;
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}
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}
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// ==================== 导出 ====================
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module.exports = {
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splitAudioStems,
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extractVoiceTrack,
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extractBgmTrack,
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extractSfxTrack,
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analyzeAudioLevels,
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suggestMixLevels,
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probeDuration,
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};
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