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pyannote/pyannote-audio

默认分支 main · commit 78c0d16a · 扫描时间 2026/5/8 13:47:03

星标 9,898 · Fork 1,057

AI 可见性总分
33 /100
亟需修复
品类召回
0 / 2
在所有问题中均未被推荐
规则结果
通过 2 · 警告 0 · 失败 0
客观元数据检查
AI 认识你的名字
2 / 3
直接询问时,AI 是否点名你的仓库
如何阅读这份报告

行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 pyannote/pyannote-audio 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。

行动计划 — 可复制粘贴的修复

3 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。

整体方向
  • highreadme#1
    Reposition the README's opening paragraph to emphasize its core differentiator

    原因:

    当前
    `pyannote.audio` is an open-source toolkit written in Python for speaker diarization. Based on PyTorch machine learning framework, it comes with state-of-the-art pretrained models and pipelines, that can be further finetuned to your own data for even better performance.
    复制粘贴的修复
    `pyannote.audio` is a highly specialized, end-to-end open-source Python toolkit for state-of-the-art speaker diarization. Built on PyTorch, it provides robust pretrained models and pipelines for tasks like speech activity detection, speaker change detection, and overlapped speech detection, which can be fine-tuned for superior performance on your own data.
  • mediumabout#2
    Refine the 'About' description to be more purpose-driven

    原因:

    当前
    Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
    复制粘贴的修复
    An open-source Python toolkit for state-of-the-art speaker diarization, offering neural building blocks for speech activity detection, speaker change detection, overlapped speech detection, and speaker embedding.
  • mediumreadme#3
    Add a concise 'What is pyannote.audio?' section to the README

    原因:

    复制粘贴的修复
    ## What is pyannote.audio?
    `pyannote.audio` is designed for researchers and developers who need to accurately identify 'who spoke when' in audio recordings. It provides a comprehensive, state-of-the-art solution for speaker diarization, including robust detection of speech activity, speaker changes, and overlapped speech.

本次扫描解析到的品类 GEO 通道:google/gemini-2.5-flash, deepseek/deepseek-v4-flash

品类可见性 — 真正的 GEO 测试

向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?

各模型使用同一组问题 — 切换标签对比回答与排名。

召回
0 / 2
0% 的问题里出现了 pyannote/pyannote-audio
平均排名
越小越好。#1 表示首位推荐。
声量占比
0%
在所有被点名的工具中,你占了多少?
头号对手
pyannote.audio
在 2 个问题中被推荐 2 次
竞品排行
  1. pyannote.audio · 被推荐 2 次
  2. SpeechBrain · 被推荐 2 次
  3. NVIDIA NeMo · 被推荐 1 次
  4. OpenVINO · 被推荐 1 次
  5. Kaldi · 被推荐 1 次
  • 品类问题
    What are the best open-source tools for identifying and segmenting different speakers in audio?
    你:未被推荐
    AI 推荐顺序:
    1. pyannote.audio
    2. NVIDIA NeMo
    3. SpeechBrain
    4. OpenVINO
    5. Kaldi
    6. wespeaker

    AI 推荐了 6 个替代方案,却始终没点名 pyannote/pyannote-audio。这就是要补上的差距。

    查看 AI 完整回答
  • 品类问题
    Looking for a robust Python library to detect speech activity and speaker changes in recordings.
    你:未被推荐
    AI 推荐顺序:
    1. pyannote.audio
    2. SpeechBrain
    3. WebRTC Voice Activity Detector
    4. OpenVAD
    5. librosa
    6. scikit-learn

    AI 推荐了 6 个替代方案,却始终没点名 pyannote/pyannote-audio。这就是要补上的差距。

    查看 AI 完整回答

客观检查

针对 AI 引擎最看重的元数据信号的规则审计。

  • Metadata completeness
    pass

  • README presence
    pass

自指检查

当被直接问到你时,AI 是否还知道你的仓库存在?

  • Compared to common alternatives in this category, what is the core differentiator of pyannote/pyannote-audio?
    pass
    AI 明确点名了 pyannote/pyannote-audio

    AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?

  • If a team adopts pyannote/pyannote-audio in production, what risks or prerequisites should they evaluate first?
    pass
    AI 明确点名了 pyannote/pyannote-audio

    AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?

  • In one sentence, what problem does the repo pyannote/pyannote-audio solve, and who is the primary audience?
    pass
    AI 未点名 pyannote/pyannote-audio —— 很可能在说另一个项目

    AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?

嵌入你的 GEO 徽章

把这个徽章贴进 pyannote/pyannote-audio 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。

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Pro

订阅 Pro,解锁深度诊断

pyannote/pyannote-audio — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。

  • 深度报告每月 10 次
  • 无品牌品类查询5,轻量 2
  • 优先行动项8,轻量 3