RRepoGEO

REPOGEO REPORT · LITE

KoljaB/RealtimeTTS

Default branch master · commit 9c96c8b9 · scanned 6/28/2026, 7:22:05 AM

GitHub: 3,970 stars · 400 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 KoljaB/RealtimeTTS, 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 first sentence to emphasize LLM streaming and multi-engine orchestration

    Why:

    CURRENT
    RealtimeTTS is a Python text-to-speech library for applications that need to turn strings, generators, and LLM token streams into audio with low latency. It can play speech locally, stream chunks to another process, write WAV files, and fall back across multiple engines.
    COPY-PASTE FIX
    RealtimeTTS is a Python library that provides a **unified, low-latency, real-time streaming interface** for converting text, generators, and especially **LLM token streams** into speech, orchestrating various local and cloud TTS engines. It can play speech locally, stream chunks to another process, write WAV files, and fall back across multiple engines.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://pypi.org/project/RealtimeTTS/
  • lowtopics#3
    Add more specific topics related to LLM streaming and multi-engine TTS

    Why:

    CURRENT
    python, realtime, speech-synthesis, text-to-speech
    COPY-PASTE FIX
    python, realtime, speech-synthesis, text-to-speech, llm-streaming, tts-streaming, multi-engine-tts

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 KoljaB/RealtimeTTS
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Amazon Polly
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Amazon Polly · recommended 2×
  2. Google Cloud Text-to-Speech · recommended 1×
  3. ElevenLabs · recommended 1×
  4. Microsoft Azure AI Speech · recommended 1×
  5. OpenAI TTS · recommended 1×
  • CATEGORY QUERY
    How can I convert streaming text from an LLM into speech with minimal latency?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Text-to-Speech
    2. Amazon Polly
    3. ElevenLabs
    4. Microsoft Azure AI Speech
    5. OpenAI TTS
    6. Deepgram Aura

    AI recommended 6 alternatives but never named KoljaB/RealtimeTTS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What Python library offers low-latency text-to-speech synthesis supporting local and cloud engines?
    you: not recommended
    AI recommended (in order):
    1. gTTS
    2. pyttsx3
    3. Azure Text-to-Speech SDK for Python
    4. Amazon Polly
    5. Coqui TTS
    6. Mozilla TTS
    7. DeepSpeech

    AI recommended 7 alternatives but never named KoljaB/RealtimeTTS. 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 KoljaB/RealtimeTTS?
    pass
    AI named KoljaB/RealtimeTTS explicitly

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

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

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

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KoljaB/RealtimeTTS — 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