REPOGEO REPORT · LITE

snakers4/silero-models

Default branch master · commit 9190f499 · scanned 6/20/2026, 10:37:13 AM

GitHub: 5,972 stars · 366 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

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 snakers4/silero-models, 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's opening to highlight unique language support

Why:

CURRENT

Our TTS models satisfy the following criteria: Fully end-to-end; Large library of voices; Natural-sounding speech; One-line usage, minimal, portable; Impressively fast on CPU and GPU; For the Russian language - automated stress and homographs;

COPY-PASTE FIX

Silero Models offers a large library of fully end-to-end, natural-sounding text-to-speech voices, with a strong focus on Eastern European and Central Asian languages. Our models are designed for one-line usage, minimal dependencies, and impressive speed on both CPU and GPU, including automated stress and homograph support for Russian.

highreadme#2

Add explicit license clarification to README

Why:

COPY-PASTE FIX

Our models are distributed under a custom license. Please refer to the [LICENSE file](https://github.com/snakers4/silero-models/blob/master/LICENSE) for full details on usage and redistribution terms.

mediumhomepage#3
Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIX
```
https://[YOUR_PROJECT_HOMEPAGE_URL_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

0 / 2

0% of queries surface snakers4/silero-models

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Google Cloud Text-to-Speech

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Google Cloud Text-to-Speech · recommended 2×
Amazon Polly · recommended 2×
coqui-ai/TTS · recommended 2×
espnet/espnet · recommended 2×
Microsoft Azure Text to Speech · recommended 1×

CATEGORY QUERY
What are good pre-trained text-to-speech models for Python to generate natural-sounding speech?
you: not recommended
AI recommended (in order):
1. Google Cloud Text-to-Speech
2. Microsoft Azure Text to Speech
3. Amazon Polly
4. Mozilla TTS (mozilla/TTS)
5. Coqui TTS (coqui-ai/TTS)
6. ESPnet (espnet/espnet)
7. OpenTTS (synesthesiam/opentts)
AI recommended 7 alternatives but never named snakers4/silero-models. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Which speech synthesis libraries offer pre-trained models for various Eastern European and Central Asian languages?
you: not recommended
AI recommended (in order):
1. Google Cloud Text-to-Speech
2. Microsoft Azure AI Speech
3. Amazon Polly
4. OpenNMT-py (OpenNMT/OpenNMT-py)
5. ESPnet (espnet/espnet)
6. Hugging Face Transformers (huggingface/transformers)
7. Coqui TTS (coqui-ai/TTS)
8. Yandex SpeechKit
9. DeepMind
AI recommended 9 alternatives but never named snakers4/silero-models. 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 snakers4/silero-models?
pass
AI named snakers4/silero-models explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts snakers4/silero-models in production, what risks or prerequisites should they evaluate first?
pass
AI named snakers4/silero-models 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 snakers4/silero-models solve, and who is the primary audience?
pass
AI named snakers4/silero-models 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 snakers4/silero-models. 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/snakers4/silero-models.svg)](https://repogeo.com/en/r/snakers4/silero-models)

HTML

<a href="https://repogeo.com/en/r/snakers4/silero-models"><img src="https://repogeo.com/badge/snakers4/silero-models.svg" alt="RepoGEO" /></a>

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snakers4/silero-models — 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