RRepoGEO

REPOGEO REPORT · LITE

boson-ai/higgs-audio

Default branch main · commit 8b1539a0 · scanned 5/14/2026, 4:03:37 PM

GitHub: 8,039 stars · 620 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 boson-ai/higgs-audio, 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
    Add explicit text-to-speech positioning to README intro

    Why:

    CURRENT
    The README's first content section after the H1 and links is '## NEWS！We are proud to launch Higgs-Audio V2.5...'
    COPY-PASTE FIX
    Add the following sentence immediately after the initial links div and before the '## NEWS!' section: 'Higgs Audio is an open-source text-to-speech (TTS) and audio generation foundation model, offering high-fidelity voice cloning and fine-grained style control for production environments.'
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    text-to-speech, tts, audio-generation, voice-cloning, deep-learning, foundation-model, ai, machine-learning
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://boson.ai/blog/higgs-audio-v2.5

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 boson-ai/higgs-audio
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
VITS
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. VITS · recommended 1×
  2. StyleTTS 2 · recommended 1×
  3. Tacotron 2 · recommended 1×
  4. WaveGlow · recommended 1×
  5. Hifi-GAN · recommended 1×
  • CATEGORY QUERY
    What open-source models provide high-fidelity text-to-speech generation with fine-grained style control?
    you: not recommended
    AI recommended (in order):
    1. VITS
    2. StyleTTS 2
    3. Tacotron 2
    4. WaveGlow
    5. Hifi-GAN
    6. Grad-TTS
    7. FastSpeech 2
    8. FastSpeech 2s

    AI recommended 8 alternatives but never named boson-ai/higgs-audio. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an efficient audio generation model for production, including voice cloning capabilities.
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs Prime Voice AI
    2. Google Cloud Text-to-Speech
    3. Azure AI Speech
    4. Resemble.ai
    5. Play.ht

    AI recommended 5 alternatives but never named boson-ai/higgs-audio. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    Suggestion:

  • 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 boson-ai/higgs-audio?
    pass
    AI named boson-ai/higgs-audio explicitly

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

  • If a team adopts boson-ai/higgs-audio in production, what risks or prerequisites should they evaluate first?
    pass
    AI named boson-ai/higgs-audio 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 boson-ai/higgs-audio solve, and who is the primary audience?
    pass
    AI named boson-ai/higgs-audio explicitly

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

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MARKDOWN (README)
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HTML
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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite