REPOGEO REPORT · LITE

WhisperSpeech/WhisperSpeech

Default branch main · commit a4596458 · scanned 7/1/2026, 12:38:06 PM

GitHub: 4,619 stars · 271 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

40 /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

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 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

Expand repository topics to improve category recall

Why:

CURRENT

pytorch, speech-synthesis, tts

COPY-PASTE FIX

pytorch, speech-synthesis, tts, open-source, text-to-speech, voice-synthesis, generative-ai, audio-generation, ai-voice, voice-cloning, multilingual-tts

highabout#2

Refine the repository description for better keyword matching

Why:

CURRENT

An Open Source text-to-speech system built by inverting Whisper.

COPY-PASTE FIX

An open-source, high-quality text-to-speech (TTS) system built by inverting Whisper, designed for natural-sounding, commercially safe voice generation.

mediumreadme#3

Add a 'How WhisperSpeech Compares' section to the README

Why:

COPY-PASTE FIX

Add a new section, e.g., '## How WhisperSpeech Compares', explaining its unique approach (inverting Whisper, multilingual, commercially safe, hackable) compared to other open-source TTS systems. For example:

## How WhisperSpeech Compares
Unlike many traditional text-to-speech systems, WhisperSpeech is built by 'inverting' OpenAI's Whisper model, leveraging its robust speech representations. This unique approach aims to deliver high-quality, natural-sounding, and commercially safe speech generation, with a focus on being as powerful and hackable for speech as Stable Diffusion is for images. We prioritize multilingual and multispeaker capabilities, making it a versatile choice for custom voice applications.

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 1 of 2 queries

COMPETITOR LEADERBOARD

Coqui TTS · recommended 1×
Mozilla TTS · recommended 1×
ESPnet · recommended 1×
OpenVocalizer · recommended 1×
Bark · recommended 1×

CATEGORY QUERY
Seeking an open-source text-to-speech system for generating natural-sounding, high-quality audio.
you: not recommended
AI recommended (in order):
1. Coqui TTS
2. Mozilla TTS
3. ESPnet
4. OpenVocalizer
5. Bark
6. MaryTTS
AI recommended 6 alternatives but never named WhisperSpeech/WhisperSpeech. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best commercially friendly text-to-speech solutions for custom voice applications?
you: not recommended
AI recommended (in order):
1. Amazon Polly
2. Google Cloud Text-to-Speech
3. Microsoft Azure Text to Speech
4. ElevenLabs
5. IBM Watson Text to Speech
6. Resemble.ai
7. WellSaid Labs
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 named WhisperSpeech/WhisperSpeech explicitly
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?

Embed your GEO score

Drop this badge into the README of WhisperSpeech/WhisperSpeech. 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/WhisperSpeech/WhisperSpeech"><img src="https://repogeo.com/badge/WhisperSpeech/WhisperSpeech.svg" alt="RepoGEO" /></a>

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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