RRepoGEO

REPOGEO REPORT · LITE

fishaudio/fish-diffusion

Default branch main · commit 8e8f8cd8 · scanned 6/7/2026, 2:51:32 AM

GitHub: 745 stars · 104 forks

AI VISIBILITY SCORE
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface fishaudio/fish-diffusion, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Refine README's opening description for clarity and differentiation

    Why:

    CURRENT
    An easy to understand TTS / SVS / SVC training framework.
    COPY-PASTE FIX
    Fish Diffusion is an easy-to-understand framework for training high-quality, natural-sounding Text-to-Speech (TTS), Singing Voice Synthesis (SVS), and Voice Conversion (SVC) models using diffusion technology, optimized for efficient inference.
  • mediumtopics#2
    Add more specific topics for better categorization

    Why:

    CURRENT
    diffusion, pytorch, soundgenerator
    COPY-PASTE FIX
    diffusion, pytorch, soundgenerator, text-to-speech, voice-synthesis, voice-conversion, singing-voice-synthesis, speech-synthesis
  • lowreadme#3
    Add a 'Key Features' section to highlight differentiators

    Why:

    COPY-PASTE FIX
    Add a new section, e.g., 'Key Features' or 'Why Fish Diffusion?', immediately after the initial description. Populate it with bullet points detailing unique aspects:
- High-quality, natural-sounding speech and singing voice generation.
- Comprehensive framework for Text-to-Speech (TTS), Singing Voice Synthesis (SVS), and Voice Conversion (SVC).
- Leverages advanced diffusion models for state-of-the-art results.
- Optimized for efficient inference, enabling real-time applications.
- Designed for ease of understanding and use by developers and researchers.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface fishaudio/fish-diffusion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenVPI/DiffSinger
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenVPI/DiffSinger · recommended 1×
  2. huggingface/diffusers · recommended 1×
  3. NVIDIA/Grad-TTS · recommended 1×
  4. OpenVPI · recommended 1×
  5. lucidrains/torchdiffusion · recommended 1×
  • CATEGORY QUERY
    Looking for an open-source framework to generate realistic speech and singing voices using diffusion models.
    you: not recommended
    AI recommended (in order):
    1. DiffSinger (OpenVPI/DiffSinger)
    2. diffusers (huggingface/diffusers)
    3. Grad-TTS (NVIDIA/Grad-TTS)
    4. OpenVPI
    5. TorchDiffusion (lucidrains/torchdiffusion)

    AI recommended 5 alternatives but never named fishaudio/fish-diffusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are some easy-to-use PyTorch libraries for voice synthesis and conversion tasks?
    you: not recommended
    AI recommended (in order):
    1. ESPnet
    2. Coqui TTS
    3. torchaudio
    4. NVIDIA NeMo
    5. PaddleSpeech

    AI recommended 5 alternatives but never named fishaudio/fish-diffusion. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of fishaudio/fish-diffusion?
    pass
    AI did not name fishaudio/fish-diffusion — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts fishaudio/fish-diffusion in production, what risks or prerequisites should they evaluate first?
    pass
    AI named fishaudio/fish-diffusion explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo fishaudio/fish-diffusion solve, and who is the primary audience?
    pass
    AI did not name fishaudio/fish-diffusion — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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  • Brand-free category queries5 vs 2 in Lite
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