RRepoGEO

REPOGEO REPORT · LITE

BinWang28/audio-ai-hub

Default branch main · commit 44bf4ffb · scanned 6/15/2026, 8:38:41 AM

GitHub: 932 stars · 48 forks

AI VISIBILITY SCORE
22 /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
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 BinWang28/audio-ai-hub, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Choose and add a standard open-source license file (e.g., MIT, Apache-2.0) to the repository root.
  • highabout#2
    Clarify the 'About' description to emphasize its role as a centralized research hub

    Why:

    CURRENT
    The hub for audio AI research: papers, open models, benchmarks & datasets across audio LLMs, speech recognition, TTS, music & audio generation.
    COPY-PASTE FIX
    A centralized, curated hub for audio AI researchers, providing papers, open models, benchmarks, and datasets across audio LLMs, speech recognition, TTS, and music & audio generation.
  • mediumtopics#3
    Add 'research' and 'datasets' to the repository topics

    Why:

    CURRENT
    audio-ai, audio-generation, audio-llm, music-generation, paper-list, speech-recognition, tts
    COPY-PASTE FIX
    audio-ai, audio-generation, audio-llm, music-generation, paper-list, speech-recognition, tts, research, datasets

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 BinWang28/audio-ai-hub
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Hub
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Hub · recommended 1×
  2. Papers With Code · recommended 1×
  3. GitHub · recommended 1×
  4. Awesome Audio AI/ML Lists · recommended 1×
  5. TensorFlow Hub · recommended 1×
  • CATEGORY QUERY
    Where can I find a curated list of open-source models for various audio AI tasks?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Hub
    2. Papers With Code
    3. GitHub
    4. Awesome Audio AI/ML Lists
    5. TensorFlow Hub
    6. PyTorch Hub

    AI recommended 6 alternatives but never named BinWang28/audio-ai-hub. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the leading research papers and datasets for modern speech synthesis or music generation?
    you: not recommended
    AI recommended (in order):
    1. Tacotron 2
    2. WaveNet
    3. FastSpeech 2
    4. VITS
    5. StyleSpeech
    6. VALL-E
    7. LJ Speech Dataset
    8. LibriTTS
    9. Common Voice
    10. VCTK Corpus
    11. Magenta
    12. MuseNet
    13. Jukebox
    14. MusicLM
    15. AudioGen
    16. Riffusion
    17. MAESTRO
    18. Lakh MIDI Dataset
    19. Pop909
    20. NSynth Dataset
    21. Free Music Archive

    AI recommended 21 alternatives but never named BinWang28/audio-ai-hub. 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 BinWang28/audio-ai-hub?
    pass
    AI did not name BinWang28/audio-ai-hub — 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 BinWang28/audio-ai-hub in production, what risks or prerequisites should they evaluate first?
    pass
    AI named BinWang28/audio-ai-hub 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 BinWang28/audio-ai-hub solve, and who is the primary audience?
    pass
    AI did not name BinWang28/audio-ai-hub — 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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Drop this badge into the README of BinWang28/audio-ai-hub. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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BinWang28/audio-ai-hub — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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