REPOGEO REPORT · LITE

WhisperSpeech/WhisperSpeech

Default branch main · commit a4596458 · scanned 5/20/2026, 2:17:41 AM

GitHub: 4,606 stars · 272 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 WhisperSpeech/WhisperSpeech, 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

hightopics#1

Add more specific and descriptive topics

Why:

CURRENT

pytorch, speech-synthesis, tts

COPY-PASTE FIX

pytorch, speech-synthesis, tts, generative-ai, voice-cloning, ai-speech, text-to-speech-system, open-source-ai, production-ready, commercial-use

highreadme#2

Add an explicit value proposition for developers and commercial use

Why:

COPY-PASTE FIX

Add this text right after the 'commercially safe.' sentence in the introduction: "Designed for developers, WhisperSpeech offers unparalleled custom control and is production-ready for commercial applications."

mediumreadme#3

Add a section highlighting core differentiators

Why:

COPY-PASTE FIX

Add a new section, e.g., '## Why WhisperSpeech?' or '## Differentiators', with points like:
*   **Built on Whisper:** Leverages OpenAI's robust Whisper encoder for high-quality, multilingual speech generation, offering a unique inversion approach.
*   **Stable Diffusion for Speech:** Aims to provide the same level of power, hackability, and commercial safety for speech generation as Stable Diffusion does for images.
*   **Open-Source & Production-Ready:** Fully open-source with permissive licenses (Apache-2.0 / MIT), designed for developers seeking custom control and commercial deployment.

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 WhisperSpeech/WhisperSpeech

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Coqui TTS

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Coqui TTS · recommended 2×
Mozilla TTS · recommended 1×
ESPnet · recommended 1×
MaryTTS · recommended 1×
OpenTTS · recommended 1×

CATEGORY QUERY
Looking for an open-source text-to-speech system for commercial applications with good quality.
you: not recommended
AI recommended (in order):
1. Mozilla TTS
2. Coqui TTS
3. ESPnet
4. MaryTTS
5. OpenTTS
AI recommended 5 alternatives but never named WhisperSpeech/WhisperSpeech. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best generative AI speech synthesis tools for developers wanting custom control?
you: not recommended
AI recommended (in order):
1. ElevenLabs
2. Google Cloud Text-to-Speech
3. Amazon Polly
4. Microsoft Azure AI Speech
5. Resemble AI
6. Play.ht
7. Coqui TTS
AI recommended 7 alternatives but never named WhisperSpeech/WhisperSpeech. 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 WhisperSpeech/WhisperSpeech?
pass
AI did not name WhisperSpeech/WhisperSpeech — 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 WhisperSpeech/WhisperSpeech in production, what risks or prerequisites should they evaluate first?
pass
AI named WhisperSpeech/WhisperSpeech 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 WhisperSpeech/WhisperSpeech solve, and who is the primary audience?
pass
AI named WhisperSpeech/WhisperSpeech explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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Pro

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WhisperSpeech/WhisperSpeech — 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