RRepoGEO

REPOGEO REPORT · LITE

Text-to-Audio/Make-An-Audio

Default branch main · commit 0d84177c · scanned 6/15/2026, 6:32:46 PM

GitHub: 668 stars · 92 forks

AI VISIBILITY SCORE
28 /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
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 Text-to-Audio/Make-An-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
    Reposition README opening to clarify project type and audience

    Why:

    CURRENT
    PyTorch Implementation of Make-An-Audio (ICML'23): a conditional diffusion probabilistic model capable of generating high fidelity audio efficiently from X modality.
    COPY-PASTE FIX
    This is the official PyTorch implementation of Make-An-Audio (ICML'23), a state-of-the-art conditional diffusion probabilistic model for high-fidelity text-to-audio generation. It is designed for researchers and developers exploring advanced generative audio models.
  • mediumtopics#2
    Add more specific technical and project-type topics

    Why:

    CURRENT
    diffusion-models, latent-diffusion, latent-space, text-to-audio, video-to-audio
    COPY-PASTE FIX
    diffusion-models, latent-diffusion, latent-space, text-to-audio, video-to-audio, pytorch, generative-ai, audio-generation, icml-2023, research-project, open-source-implementation
  • lowhomepage#3
    Add the project's homepage URL

    Why:

    COPY-PASTE FIX
    https://huggingface.co/spaces/AIGC-Audio/Make_An_Audio

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 Text-to-Audio/Make-An-Audio
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ElevenLabs Text to Speech
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ElevenLabs Text to Speech · recommended 1×
  2. Google Cloud Text-to-Speech · recommended 1×
  3. Microsoft Azure AI Speech · recommended 1×
  4. Meta Voicebox · recommended 1×
  5. OpenAI TTS · recommended 1×
  • CATEGORY QUERY
    How can I generate realistic audio from text prompts using deep learning models?
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs Text to Speech
    2. Google Cloud Text-to-Speech
    3. Microsoft Azure AI Speech
    4. Meta Voicebox
    5. OpenAI TTS
    6. Coqui TTS
    7. Amazon Polly

    AI recommended 7 alternatives but never named Text-to-Audio/Make-An-Audio. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source PyTorch libraries exist for high-fidelity text-to-audio synthesis with diffusion?
    you: not recommended
    AI recommended (in order):
    1. AudioGen
    2. AudioLDM / AudioLDM 2
    3. Diffusers
    4. Riffusion
    5. Matcha-TTS

    AI recommended 5 alternatives but never named Text-to-Audio/Make-An-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 Text-to-Audio/Make-An-Audio?
    pass
    AI named Text-to-Audio/Make-An-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 Text-to-Audio/Make-An-Audio in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Text-to-Audio/Make-An-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 Text-to-Audio/Make-An-Audio solve, and who is the primary audience?
    pass
    AI did not name Text-to-Audio/Make-An-Audio — 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?

Embed your GEO score

Drop this badge into the README of Text-to-Audio/Make-An-Audio. 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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MARKDOWN (README)
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Text-to-Audio/Make-An-Audio — 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