REPOGEO REPORT · LITE

seungwonpark/melgan

Default branch master · commit aca59909 · scanned 5/30/2026, 7:21:40 PM

GitHub: 650 stars · 113 forks

AI VISIBILITY SCORE

59 /100

Needs work

Category recall

1 / 2

Avg rank #6.0 when recommended

Rule findings

2 pass · 0 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 seungwonpark/melgan, 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 core value proposition in README's opening

Why:

CURRENT

# MelGAN
Unofficial PyTorch implementation of MelGAN vocoder

COPY-PASTE FIX

# MelGAN: A Fast, High-Quality PyTorch Vocoder
Unofficial PyTorch implementation of MelGAN, a vocoder that is lighter, faster, and better at generalizing to unseen speakers than WaveGlow.

mediumtopics#2
Add more specific topics related to speed and quality
Why:
CURRENT
```
gan, neural-vocoder, pytorch, tts
```
COPY-PASTE FIX
```
gan, neural-vocoder, pytorch, tts, fast-audio-synthesis, high-fidelity-audio
```
lowexamples#3
Complete the Google Colab example in the README
Why:
CURRENT
```
Try with Google Colab: TODO
```
COPY-PASTE FIX
```
Try with Google Colab: [Add link to a working Colab notebook here]
```

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

1 / 2

50% of queries surface seungwonpark/melgan

Avg rank

#6.0

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

jik876/hifi-gan

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

jik876/hifi-gan · recommended 1×
NVIDIA/BigVGAN · recommended 1×
mindslab-ai/univnet · recommended 1×
kan-bayashi/ParallelWaveGAN · recommended 1×
NVIDIA/waveglow · recommended 1×

CATEGORY QUERY
Looking for a fast PyTorch vocoder to convert mel-spectrograms into high-quality raw audio.
you: not recommended
AI recommended (in order):
1. Hifi-GAN (jik876/hifi-gan)
2. BigVGAN (NVIDIA/BigVGAN)
3. UnivNet (mindslab-ai/univnet)
4. Parallel WaveGAN (kan-bayashi/ParallelWaveGAN)
5. WaveGlow (NVIDIA/waveglow)
AI recommended 5 alternatives but never named seungwonpark/melgan. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are good neural vocoders for converting Tacotron2 output efficiently to speech?
you: #6
AI recommended (in order):
1. Hifi-GAN
2. UnivNet
3. BigVGAN
4. Parallel WaveGAN (PWG)
5. WaveGlow
6. MelGAN ← you
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 seungwonpark/melgan?
pass
AI named seungwonpark/melgan explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts seungwonpark/melgan in production, what risks or prerequisites should they evaluate first?
pass
AI named seungwonpark/melgan 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 seungwonpark/melgan solve, and who is the primary audience?
pass
AI named seungwonpark/melgan 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 seungwonpark/melgan. 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)

[![RepoGEO](https://repogeo.com/badge/seungwonpark/melgan.svg)](https://repogeo.com/en/r/seungwonpark/melgan)

HTML

<a href="https://repogeo.com/en/r/seungwonpark/melgan"><img src="https://repogeo.com/badge/seungwonpark/melgan.svg" alt="RepoGEO" /></a>

Pro

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seungwonpark/melgan — 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