sanbuphy
084ebed417
- Update AI capability dictionary by removing redundant mention of Baidu's model - Add new Vue components for context engineering visualization (IntroProblemReasonSolution, MemoryPalaceDemo, MemoryPalaceActionDemo, KVCacheDemo, LostInMiddleDemo) - Register new components in theme index.js - Enhance audio introduction with new interactive demos (AudioQuickStartDemo, MelSpectrogramDemo, TTSPipelineDemo, VoiceCloningDemo, ASRvsTTSDemo, AudioTokenizationDemo, EmotionControlDemo) - Improve existing context engineering demos with Chinese localization and better tokenization - Fix Japanese documentation layout by properly closing NavGrid components
688 lines
16 KiB
Vue
688 lines
16 KiB
Vue
<!--
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AudioTokenizationDemo.vue
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音频 Tokenization 演示组件
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用途：
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展示音频如何通过神经编解码器(如 EnCodec、SoundStream)被压缩成离散的 Token。
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交互功能：
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- 音频压缩/解压流程
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- 不同码率对比
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- Token 可视化
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- 重建质量评估
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-->
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<template>
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<div class="audio-tokenization-demo">
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<el-card shadow="never">
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<template #header>
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<div class="header-title">
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<el-icon><Grid /></el-icon>
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<span>🎵 音频 Tokenization：神经编解码器</span>
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</div>
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</template>
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<div class="demo-content">
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<!-- 流程图 -->
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<div class="codec-flow">
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<div class="flow-section encode">
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<div class="section-title">🔽 编码器 (Encoder)</div>
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<div class="flow-steps">
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<div class="codec-step">
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<div class="step-visual">
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<canvas ref="originalWaveformCanvas" width="150" height="60" />
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</div>
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<div class="step-label">原始波形</div>
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<div class="step-meta">24kHz, 16-bit</div>
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</div>
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<el-icon class="flow-arrow"><ArrowRight /></el-icon>
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<div class="codec-step">
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<div class="step-visual">
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<div class="cnn-layers">
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<div class="cnn-layer" v-for="i in 4" :key="i" :style="{ opacity: 0.3 + i * 0.2 }">
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Conv {{ i }}
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</div>
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</div>
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</div>
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<div class="step-label">CNN 下采样</div>
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<div class="step-meta">降维 320x</div>
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</div>
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<el-icon class="flow-arrow"><ArrowRight /></el-icon>
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<div class="codec-step">
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<div class="step-visual">
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<div class="vq-codebook">
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<div class="codebook-grid">
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<div
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v-for="i in 16"
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:key="i"
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class="codebook-cell"
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:class="{ active: i <= 4 }"
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/>
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</div>
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</div>
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</div>
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<div class="step-label">VQ 量化</div>
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<div class="step-meta">离散 Token</div>
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</div>
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</div>
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</div>
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<div class="flow-divider">
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<div class="divider-line"></div>
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<div class="divider-label">压缩后: ~1.5 kbps</div>
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<div class="divider-line"></div>
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</div>
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<div class="flow-section decode">
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<div class="section-title">🔼 解码器 (Decoder)</div>
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<div class="flow-steps reverse">
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<div class="codec-step">
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<div class="step-visual">
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<div class="token-sequence">
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<span
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v-for="(token, i) in [42, 128, 7, 255, 33, 91]"
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:key="i"
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class="token"
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:style="{ background: `hsl(${token}, 70%, 50%)` }"
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>
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{{ token }}
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</span>
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</div>
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</div>
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<div class="step-label">离散 Token</div>
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<div class="step-meta">Codebook 索引</div>
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</div>
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<el-icon class="flow-arrow"><ArrowRight /></el-icon>
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<div class="codec-step">
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<div class="step-visual">
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<div class="cnn-layers">
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<div class="cnn-layer" v-for="i in 4" :key="i" :style="{ opacity: 1 - i * 0.15 }">
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ConvT {{ 5 - i }}
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</div>
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</div>
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</div>
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<div class="step-label">转置卷积</div>
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<div class="step-meta">上采样</div>
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</div>
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<el-icon class="flow-arrow"><ArrowRight /></el-icon>
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<div class="codec-step">
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<div class="step-visual">
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<canvas ref="reconstructedWaveformCanvas" width="150" height="60" />
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</div>
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<div class="step-label">重建波形</div>
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<div class="step-meta">24kHz</div>
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</div>
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</div>
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</div>
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</div>
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<!-- 码率对比 -->
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<div class="bitrate-comparison">
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<div class="comparison-title">📊 不同码率对比</div>
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<div class="bitrate-cards">
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<div
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v-for="config in bitrateConfigs"
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:key="config.name"
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class="bitrate-card"
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:class="{ active: selectedBitrate === config.name }"
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@click="selectedBitrate = config.name"
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>
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<div class="bitrate-value">{{ config.bitrate }}</div>
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<div class="bitrate-name">{{ config.name }}</div>
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<div class="bitrate-detail">
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<div class="detail-item">
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<span class="label">采样率:</span>
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<span>{{ config.sampleRate }}</span>
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</div>
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<div class="detail-item">
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<span class="label">帧率:</span>
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<span>{{ config.frameRate }}</span>
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</div>
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<div class="detail-item">
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<span class="label">码本大小:</span>
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<span>{{ config.codebookSize }}</span>
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</div>
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</div>
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<el-rate
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v-model="config.quality"
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disabled
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show-score
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text-color="#ff9900"
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/>
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</div>
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</div>
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</div>
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<!-- Token 可视化 -->
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<div class="token-visualization">
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<div class="viz-title">🔢 Token 序列可视化</div>
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<div class="token-display">
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<div class="token-ruler">
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<span v-for="i in 20" :key="i" class="ruler-mark">{{ i * 0.1 }}s</span>
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</div>
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<div class="token-stream">
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<div
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v-for="(token, i) in tokenSequence"
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:key="i"
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class="token-block"
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:style="{
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background: `hsl(${token % 360}, 70%, ${50 + (token % 20)}%)`,
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height: `${20 + (token % 30)}px`
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}"
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:title="`Token: ${token}`"
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/>
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</div>
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</div>
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<div class="token-legend">
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<span class="legend-item">
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<span class="legend-color" style="background: #409eff"></span>
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低频成分
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</span>
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<span class="legend-item">
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<span class="legend-color" style="background: #67c23a"></span>
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中频成分
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</span>
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<span class="legend-item">
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<span class="legend-color" style="background: #e6a23c"></span>
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高频成分
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</span>
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</div>
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</div>
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<!-- 应用场景 -->
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<div class="applications">
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<div class="apps-title">🎯 为什么需要音频 Tokenization？</div>
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<div class="apps-grid">
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<div class="app-card">
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<div class="app-icon">🚀</div>
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<div class="app-title">高效传输</div>
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<div class="app-desc">
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将音频压缩到 ~1.5 kbps，比原始音频小 256 倍，适合网络传输
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</div>
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</div>
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<div class="app-card">
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<div class="app-icon">🧠</div>
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<div class="app-title">语言模型友好</div>
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<div class="app-desc">
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离散 Token 可以被 LLM 直接处理，实现文本到音频的统一建模
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</div>
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</div>
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<div class="app-card">
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<div class="app-icon">🎵</div>
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<div class="app-title">音乐生成</div>
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<div class="app-desc">
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MusicGen、AudioLDM 等模型使用音频 Token 生成音乐和音效
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</div>
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</div>
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<div class="app-card">
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<div class="app-icon">🗣️</div>
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<div class="app-title">语音合成</div>
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<div class="app-desc">
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VALL-E、SoundStorm 等 TTS 模型直接生成音频 Token
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</div>
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</div>
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</div>
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</div>
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</div>
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<div class="info-box">
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<p>
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<span class="icon">💡</span>
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<strong>神经音频编解码器：</strong>
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EnCodec (Meta)、SoundStream (Google)、SNAC 等模型使用 VQ-VAE 架构将音频压缩成离散 Token。这些 Token 可以被语言模型处理，实现高质量的音频生成和压缩。
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</p>
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</div>
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</el-card>
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</div>
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</template>
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<script setup>
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import { ref, onMounted } from 'vue'
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import { Grid, ArrowRight } from '@element-plus/icons-vue'
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const selectedBitrate = ref('EnCodec-24k')
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const originalWaveformCanvas = ref(null)
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const reconstructedWaveformCanvas = ref(null)
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const bitrateConfigs = [
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{
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name: 'EnCodec-24k',
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bitrate: '1.5 kbps',
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sampleRate: '24 kHz',
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frameRate: '75 Hz',
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codebookSize: '1024',
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quality: 4
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},
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{
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name: 'EnCodec-48k',
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bitrate: '3.0 kbps',
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sampleRate: '48 kHz',
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frameRate: '75 Hz',
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codebookSize: '1024',
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quality: 5
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},
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{
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name: 'SoundStream',
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bitrate: '6.0 kbps',
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sampleRate: '16 kHz',
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frameRate: '50 Hz',
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codebookSize: '1024',
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quality: 4.5
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},
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{
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name: 'SNAC',
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bitrate: '0.98 kbps',
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sampleRate: '24 kHz',
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frameRate: '43 Hz',
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codebookSize: '4096',
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quality: 4
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}
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]
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// 生成模拟 Token 序列
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const tokenSequence = Array.from({ length: 50 }, () => Math.floor(Math.random() * 1024))
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// 绘制波形
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const drawWaveform = (canvas, isNoisy = false) => {
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if (!canvas) return
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const ctx = canvas.getContext('2d')
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const width = canvas.width
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const height = canvas.height
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ctx.clearRect(0, 0, width, height)
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ctx.strokeStyle = '#409eff'
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ctx.lineWidth = 1.5
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ctx.beginPath()
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for (let x = 0; x < width; x++) {
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const t = x / width
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let y = height / 2
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// 基础波形
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y += Math.sin(t * Math.PI * 8) * 15
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y += Math.sin(t * Math.PI * 16) * 10
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// 添加噪声（重建版本）
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if (isNoisy) {
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y += (Math.random() - 0.5) * 8
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}
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if (x === 0) {
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ctx.moveTo(x, y)
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} else {
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ctx.lineTo(x, y)
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}
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}
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ctx.stroke()
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// 中心线
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ctx.strokeStyle = '#e0e0e0'
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ctx.lineWidth = 1
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ctx.beginPath()
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ctx.moveTo(0, height / 2)
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ctx.lineTo(width, height / 2)
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ctx.stroke()
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}
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onMounted(() => {
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drawWaveform(originalWaveformCanvas.value, false)
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drawWaveform(reconstructedWaveformCanvas.value, true)
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})
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</script>
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<style scoped>
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.audio-tokenization-demo {
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margin: 1rem 0;
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}
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.header-title {
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display: flex;
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align-items: center;
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gap: 8px;
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font-weight: 600;
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}
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.demo-content {
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display: flex;
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flex-direction: column;
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gap: 24px;
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}
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.codec-flow {
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background: var(--vp-c-bg-soft);
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border-radius: 8px;
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padding: 20px;
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}
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.flow-section {
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margin-bottom: 16px;
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}
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.section-title {
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font-weight: 500;
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margin-bottom: 16px;
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color: var(--vp-c-brand);
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}
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.flow-steps {
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display: flex;
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align-items: center;
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justify-content: center;
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gap: 16px;
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flex-wrap: wrap;
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}
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.flow-steps.reverse {
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flex-direction: row-reverse;
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}
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.codec-step {
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text-align: center;
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min-width: 120px;
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}
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.step-visual {
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background: var(--vp-c-bg);
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border-radius: 8px;
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padding: 12px;
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margin-bottom: 8px;
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min-height: 80px;
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display: flex;
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align-items: center;
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justify-content: center;
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}
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.step-visual canvas {
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width: 100%;
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height: auto;
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}
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.step-label {
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font-weight: 500;
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font-size: 0.875rem;
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}
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.step-meta {
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font-size: 0.75rem;
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color: var(--vp-c-text-3);
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}
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.flow-arrow {
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color: var(--vp-c-text-3);
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}
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.cnn-layers {
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display: flex;
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flex-direction: column;
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gap: 4px;
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}
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.cnn-layer {
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background: #409eff;
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color: white;
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padding: 4px 8px;
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border-radius: 4px;
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font-size: 0.7rem;
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}
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.vq-codebook {
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padding: 8px;
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}
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.codebook-grid {
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display: grid;
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grid-template-columns: repeat(4, 1fr);
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gap: 4px;
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}
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.codebook-cell {
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width: 16px;
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height: 16px;
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background: #e0e0e0;
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border-radius: 2px;
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}
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.codebook-cell.active {
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background: #67c23a;
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}
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.token-sequence {
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display: flex;
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gap: 4px;
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flex-wrap: wrap;
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max-width: 120px;
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}
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.token {
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padding: 2px 6px;
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border-radius: 4px;
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font-size: 0.7rem;
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color: white;
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font-family: monospace;
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}
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.flow-divider {
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display: flex;
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align-items: center;
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gap: 16px;
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margin: 16px 0;
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}
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.divider-line {
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flex: 1;
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height: 1px;
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background: var(--vp-c-divider);
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}
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.divider-label {
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font-size: 0.875rem;
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color: var(--vp-c-text-3);
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white-space: nowrap;
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}
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.bitrate-comparison {
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background: var(--vp-c-bg-soft);
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border-radius: 8px;
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padding: 20px;
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}
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.comparison-title {
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font-weight: 500;
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margin-bottom: 16px;
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text-align: center;
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}
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.bitrate-cards {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(180px, 1fr));
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gap: 16px;
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}
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.bitrate-card {
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background: var(--vp-c-bg);
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border-radius: 8px;
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padding: 16px;
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text-align: center;
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cursor: pointer;
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transition: all 0.2s;
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border: 2px solid transparent;
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}
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.bitrate-card:hover {
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border-color: var(--vp-c-brand);
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}
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.bitrate-card.active {
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border-color: var(--vp-c-brand);
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background: var(--vp-c-bg-mute);
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}
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.bitrate-value {
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font-size: 1.5rem;
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font-weight: 600;
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color: var(--vp-c-brand);
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margin-bottom: 4px;
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}
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.bitrate-name {
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font-weight: 500;
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margin-bottom: 12px;
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}
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.bitrate-detail {
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font-size: 0.75rem;
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color: var(--vp-c-text-3);
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margin-bottom: 12px;
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}
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.detail-item {
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display: flex;
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justify-content: space-between;
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||
padding: 2px 0;
|
||
}
|
||
|
||
.detail-item .label {
|
||
color: var(--vp-c-text-2);
|
||
}
|
||
|
||
.token-visualization {
|
||
background: var(--vp-c-bg-soft);
|
||
border-radius: 8px;
|
||
padding: 20px;
|
||
}
|
||
|
||
.viz-title {
|
||
font-weight: 500;
|
||
margin-bottom: 16px;
|
||
text-align: center;
|
||
}
|
||
|
||
.token-display {
|
||
background: var(--vp-c-bg);
|
||
border-radius: 8px;
|
||
padding: 16px;
|
||
overflow-x: auto;
|
||
}
|
||
|
||
.token-ruler {
|
||
display: flex;
|
||
gap: 8px;
|
||
margin-bottom: 8px;
|
||
font-size: 0.7rem;
|
||
color: var(--vp-c-text-3);
|
||
}
|
||
|
||
.ruler-mark {
|
||
min-width: 30px;
|
||
}
|
||
|
||
.token-stream {
|
||
display: flex;
|
||
gap: 2px;
|
||
align-items: flex-end;
|
||
height: 60px;
|
||
}
|
||
|
||
.token-block {
|
||
flex: 1;
|
||
min-width: 8px;
|
||
border-radius: 2px;
|
||
transition: all 0.2s;
|
||
}
|
||
|
||
.token-block:hover {
|
||
transform: scaleY(1.2);
|
||
z-index: 1;
|
||
}
|
||
|
||
.token-legend {
|
||
display: flex;
|
||
justify-content: center;
|
||
gap: 24px;
|
||
margin-top: 16px;
|
||
}
|
||
|
||
.legend-item {
|
||
display: flex;
|
||
align-items: center;
|
||
gap: 8px;
|
||
font-size: 0.875rem;
|
||
}
|
||
|
||
.legend-color {
|
||
width: 16px;
|
||
height: 16px;
|
||
border-radius: 4px;
|
||
}
|
||
|
||
.applications {
|
||
background: var(--vp-c-bg-soft);
|
||
border-radius: 8px;
|
||
padding: 20px;
|
||
}
|
||
|
||
.apps-title {
|
||
font-weight: 500;
|
||
margin-bottom: 16px;
|
||
text-align: center;
|
||
}
|
||
|
||
.apps-grid {
|
||
display: grid;
|
||
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
|
||
gap: 16px;
|
||
}
|
||
|
||
.app-card {
|
||
background: var(--vp-c-bg);
|
||
border-radius: 8px;
|
||
padding: 16px;
|
||
text-align: center;
|
||
}
|
||
|
||
.app-icon {
|
||
font-size: 2rem;
|
||
margin-bottom: 8px;
|
||
}
|
||
|
||
.app-title {
|
||
font-weight: 600;
|
||
margin-bottom: 8px;
|
||
}
|
||
|
||
.app-desc {
|
||
font-size: 0.8rem;
|
||
color: var(--vp-c-text-3);
|
||
line-height: 1.5;
|
||
}
|
||
|
||
.info-box {
|
||
margin-top: 16px;
|
||
padding: 12px;
|
||
background: var(--vp-c-bg-mute);
|
||
border-radius: 6px;
|
||
font-size: 0.9rem;
|
||
line-height: 1.6;
|
||
}
|
||
|
||
.icon {
|
||
font-size: 1.2em;
|
||
}
|
||
|
||
@media (max-width: 640px) {
|
||
.flow-steps {
|
||
flex-direction: column;
|
||
}
|
||
|
||
.flow-steps.reverse {
|
||
flex-direction: column;
|
||
}
|
||
|
||
.flow-arrow {
|
||
transform: rotate(90deg);
|
||
}
|
||
}
|
||
</style>
|