RRepoGEO

REPOGEO REPORT · LITE

matatonic/openedai-speech

Default branch main · commit 31f03359 · scanned 6/15/2026, 3:37:31 PM

GitHub: 858 stars · 130 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 matatonic/openedai-speech, 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 project status notice to clarify its functional description

    Why:

    CURRENT
    # OpenedAI Speech

Notice: This software is mostly obsolete and will no longer be updated.

Some Alternatives:

* https://speaches.ai/
* https://github.com/remsky/Kokoro-FastAPI
* https://github.com/astramind-ai/Auralis
* https://lightning.ai/docs/litserve/home?code_sample=speech

An OpenAI API compatible text to speech server.
    COPY-PASTE FIX
    # OpenedAI Speech

An OpenAI API compatible text to speech server.

* Compatible with the OpenAI audio/speech API
* Serves the /v1/audio/speech endpoint
* Not affiliated with OpenAI in any way, does not require an OpenAI API Key
* A free, private, text-to-speech server with custom voice cloning

Notice: This software is mostly obsolete and will no longer be updated. Consider the following alternatives for new projects:

* https://speaches.ai/
* https://github.com/remsky/Kokoro-FastAPI
* https://github.com/astramind-ai/Auralis
* https://lightning.ai/docs/litserve/home?code_sample=speech
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    openai-api-compatible, text-to-speech, tts-server, self-hosted, voice-cloning, coqui-tts, piper-tts, xtts-v2, local-ai, speech-synthesis
  • mediumhomepage#3
    Add a homepage URL for improved metadata completeness

    Why:

    COPY-PASTE FIX
    https://github.com/matatonic/openedai-speech

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 matatonic/openedai-speech
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA/DeepLearningExamples
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA/DeepLearningExamples · recommended 2×
  2. rhasspy/piper · recommended 1×
  3. coqui-ai/TTS · recommended 1×
  4. huggingface/transformers · recommended 1×
  5. espnet/espnet · recommended 1×
  • CATEGORY QUERY
    How can I self-host an OpenAI compatible text-to-speech service for my application?
    you: not recommended
    AI recommended (in order):
    1. Piper (rhasspy/piper)
    2. Coqui TTS (coqui-ai/TTS)
    3. Bark (huggingface/transformers)
    4. ESPnet (espnet/espnet)
    5. Tacotron 2 (NVIDIA/DeepLearningExamples)
    6. WaveGlow (NVIDIA/DeepLearningExamples)
    7. NVIDIA Triton Inference Server (triton-inference-server/server)

    AI recommended 7 alternatives but never named matatonic/openedai-speech. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a private text-to-speech server with custom voice cloning, runnable on local hardware.
    you: not recommended
    AI recommended (in order):
    1. Coqui TTS
    2. Mycroft Mimic 3
    3. NVIDIA Riva
    4. OpenVoice
    5. TensorFlow TTS
    6. PyTorch TTS

    AI recommended 6 alternatives but never named matatonic/openedai-speech. 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 matatonic/openedai-speech?
    pass
    AI named matatonic/openedai-speech explicitly

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

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

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

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