RRepoGEO

REPOGEO REPORT · LITE

haoheliu/AudioLDM

Default branch main · commit 4054cb41 · scanned 6/23/2026, 9:18:11 AM

GitHub: 2,891 stars · 266 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
33 /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
2 / 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 haoheliu/AudioLDM, 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 a clear statement about Latent Diffusion Model (LDM) in README intro

    Why:

    CURRENT
    **Generate speech, sound effects, music and beyond.**
    COPY-PASTE FIX
    **AudioLDM is a Latent Diffusion Model (LDM) for audio generation, enabling high-quality synthesis of speech, sound effects, music, and beyond from text descriptions.**
  • hightopics#2
    Expand repository topics for better categorization

    Why:

    CURRENT
    audio-generation
    COPY-PASTE FIX
    audio-generation, text-to-audio, speech-synthesis, sound-effects, music-generation, latent-diffusion-model, deep-learning, icml-2023
  • mediumreadme#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    ## License
This project is licensed under [insert specific license name(s) here, e.g., MIT License and Apache 2.0 License]. Please refer to the [LICENSE](LICENSE) file for full details.

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 haoheliu/AudioLDM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
facebookresearch/audiocraft
Recommended in 4 of 2 queries
COMPETITOR LEADERBOARD
  1. facebookresearch/audiocraft · recommended 4×
  2. ElevenLabs · recommended 1×
  3. Google AudioLM · recommended 1×
  4. SoundStorm · recommended 1×
  5. AIVA · recommended 1×
  • CATEGORY QUERY
    What tools are available for generating realistic sound effects, speech, and music from text descriptions?
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs
    2. Meta AudioCraft (facebookresearch/audiocraft)
    3. AudioGen (facebookresearch/audiocraft)
    4. MusicGen (facebookresearch/audiocraft)
    5. EnCodec (facebookresearch/audiocraft)
    6. Google AudioLM
    7. SoundStorm
    8. AIVA
    9. Soundraw
    10. Descript
    11. Overdub
    12. Adobe Project VoCo
    13. Adobe Audition

    AI recommended 13 alternatives but never named haoheliu/AudioLDM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I perform audio-to-audio style transfer guided by a natural language text prompt?
    you: not recommended
    AI recommended (in order):
    1. Riffusion
    2. AudioGen
    3. MusicGen
    4. Jukebox
    5. DDSP
    6. TensorFlow Magenta's DDSP library
    7. CLIP
    8. Hugging Face Transformers Audio Models
    9. Stable Diffusion

    AI recommended 9 alternatives but never named haoheliu/AudioLDM. 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 haoheliu/AudioLDM?
    pass
    AI did not name haoheliu/AudioLDM — 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 haoheliu/AudioLDM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named haoheliu/AudioLDM 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 haoheliu/AudioLDM solve, and who is the primary audience?
    pass
    AI named haoheliu/AudioLDM explicitly

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

Embed your GEO score

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haoheliu/AudioLDM — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite