RRepoGEO

REPOGEO REPORT · LITE

lmnt-com/diffwave

Default branch master · commit 05941060 · scanned 6/4/2026, 8:23:01 AM

GitHub: 887 stars · 131 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 lmnt-com/diffwave, 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 the README's opening paragraph to highlight its unique approach

    Why:

    CURRENT
    DiffWave is a fast, high-quality neural vocoder and waveform synthesizer. We're hiring! If you like what we're building here, come join us at LMNT.
    COPY-PASTE FIX
    DiffWave is a fast, high-quality neural vocoder and waveform synthesizer, leveraging **Diffusion Probabilistic Models** for state-of-the-art audio generation. It offers a unique approach for converting acoustic features to speech, providing both speed and fidelity, and stands as a robust alternative to traditional GANs or autoregressive models.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://lmnt.com
  • mediumreadme#3
    Add a 'Key Advantages' section to the README

    Why:

    COPY-PASTE FIX
    ## Key Advantages

DiffWave distinguishes itself through:
- **Diffusion Probabilistic Models:** A novel approach to audio synthesis, offering high fidelity and robustness.
- **Fast, High-Quality Synthesis:** Achieves real-time factors below 1.0, making it suitable for demanding applications.
- **Versatile:** Supports both conditional (e.g., Mel spectrogram) and unconditional waveform synthesis.
- **Production-Ready:** Includes stable training, mixed-precision, multi-GPU support, and a PyPI package.

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 lmnt-com/diffwave
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hifi-GAN
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hifi-GAN · recommended 1×
  2. BigVGAN · recommended 1×
  3. UnivNet · recommended 1×
  4. Parallel WaveGAN · recommended 1×
  5. WaveRNN · recommended 1×
  • CATEGORY QUERY
    Need a fast, high-quality neural vocoder for converting acoustic features to speech.
    you: not recommended
    AI recommended (in order):
    1. Hifi-GAN
    2. BigVGAN
    3. UnivNet
    4. Parallel WaveGAN
    5. WaveRNN
    6. MelGAN

    AI recommended 6 alternatives but never named lmnt-com/diffwave. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are robust deep learning frameworks for high-fidelity speech waveform synthesis?
    you: not recommended
    AI recommended (in order):
    1. PyTorch (pytorch/pytorch)
    2. TensorFlow (tensorflow/tensorflow)
    3. JAX (google/jax)
    4. PaddlePaddle (PaddlePaddle/Paddle)
    5. MXNet (apache/mxnet)

    AI recommended 5 alternatives but never named lmnt-com/diffwave. 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 lmnt-com/diffwave?
    pass
    AI named lmnt-com/diffwave explicitly

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

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

    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 lmnt-com/diffwave. 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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HTML
<a href="https://repogeo.com/en/r/lmnt-com/diffwave"><img src="https://repogeo.com/badge/lmnt-com/diffwave.svg" alt="RepoGEO" /></a>
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lmnt-com/diffwave — 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