flykhan
2536c937e3
翻译自英文原版 maths-cs-ai-compendium，共 20 章全部完成。 第01章 向量 | 第02章 矩阵 | 第03章 微积分 第04章 统计学 | 第05章 概率论 | 第06章 机器学习 第07章 计算语言学 | 第08章 计算机视觉 | 第09章 音频与语音 第10章 多模态学习 | 第11章 自主系统 | 第12章 图神经网络 第13章 计算与操作系统 | 第14章 数据结构与算法 第15章 生产级软件工程 | 第16章 SIMD与GPU编程 第17章 AI推理 | 第18章 ML系统设计 第19章 应用人工智能 | 第20章 前沿人工智能 翻译说明： - 所有数学公式 $...$ / $$...$$、代码块、图片引用完整保留 - mkdocs.yml 配置中文导航 + language: zh - README.md 已翻译为中文（兼 docs/index.md） - docs/ 目录包含指向各章文件的 symlink - 约 29,000 行中文内容，排除 .cache/ 构建缓存
96 lines
6.5 KiB
XML
96 lines
6.5 KiB
XML
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<!-- Title -->
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<text x="350" y="22" text-anchor="middle" font-size="14" font-weight="bold" fill="#333">Audio Spectrogram Transformer (AST)</text>
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<text x="60" y="167" text-anchor="middle" font-size="7" fill="#666">(patch grid)</text>
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<text x="153" y="86" text-anchor="middle" font-size="8" fill="#333">Flatten</text>
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<!-- Linear Projection + Pos Emb -->
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<text x="243" y="78" text-anchor="middle" font-size="8" fill="#333">Linear</text>
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<text x="243" y="89" text-anchor="middle" font-size="8" fill="#333">Projection</text>
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<!-- [CLS] token indicator -->
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<text x="255" y="122" font-size="7" fill="#666">prepended</text>
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<!-- Transformer Encoder -->
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<text x="378" y="65" text-anchor="middle" font-size="10" font-weight="bold" fill="#333">Transformer</text>
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<text x="378" y="100" text-anchor="middle" font-size="7" fill="#666">Multi-Head Attn + FFN</text>
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<text x="378" y="120" text-anchor="middle" font-size="7" fill="#666">x L layers</text>
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<text x="515" y="82" text-anchor="middle" font-size="9" fill="#333">Classification</text>
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<text x="515" y="110" text-anchor="middle" font-size="7" fill="#666">(from [CLS])</text>
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<text x="620" y="90" text-anchor="middle" font-size="9" fill="#333">Predicted</text>
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<text x="60" y="185" text-anchor="middle" font-size="7" fill="#f39c12">2D input</text>
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<text x="153" y="185" text-anchor="middle" font-size="7" fill="#3498db">sequence</text>
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<text x="243" y="185" text-anchor="middle" font-size="7" fill="#3498db">embed</text>
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<text x="378" y="185" text-anchor="middle" font-size="7" fill="#9b59b6">encode</text>
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<text x="50" y="220" font-size="10" font-weight="bold" fill="#333">AST adapts ViT (chapter 08) directly to audio spectrograms</text>
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<text x="50" y="236" font-size="9" fill="#666">No convolutions needed. The spectrogram is split into 16x16 patches, linearly projected, and processed</text>
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<text x="50" y="248" font-size="9" fill="#666">by a standard Transformer encoder. Pre-training on ImageNet transfers surprisingly well to audio.</text>
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