RRepoGEO

REPOGEO REPORT · LITE

davabase/whisper_real_time

Default branch master · commit bfc75c0d · scanned 5/9/2026, 4:22:42 PM

GitHub: 2,931 stars · 482 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 davabase/whisper_real_time, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening paragraph to clarify scope

    Why:

    CURRENT
    # Real Time Whisper Transcription

This is a demo of real time speech to text with OpenAI's Whisper model. It works by constantly recording audio in a thread and concatenating the raw bytes over multiple recordings.
    COPY-PASTE FIX
    # Real Time Whisper Transcription

This Python application provides low-latency, real-time speech-to-text transcription using OpenAI's Whisper model, designed for local execution. It continuously records audio and processes it in real-time, making it ideal for integrating live transcription capabilities into Python projects.
  • highlicense#2
    Create a LICENSE file explicitly stating 'Public Domain'

    Why:

    COPY-PASTE FIX
    Create a new file named `LICENSE` in the repository root with the content: `This code is dedicated to the public domain.`

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 davabase/whisper_real_time
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
openai/whisper
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. openai/whisper · recommended 2×
  2. AssemblyAI · recommended 2×
  3. AWS Transcribe · recommended 2×
  4. OpenAI API · recommended 1×
  5. Google Cloud Speech-to-Text · recommended 1×
  • CATEGORY QUERY
    How can I implement live audio transcription for a Python application?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Whisper (openai/whisper)
    2. OpenAI API
    3. Google Cloud Speech-to-Text
    4. AssemblyAI
    5. AWS Transcribe
    6. Vosk (alphacep/vosk-api)
    7. DeepSpeech (mozilla/DeepSpeech)

    AI recommended 7 alternatives but never named davabase/whisper_real_time. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tool to transcribe spoken words from a microphone in real-time.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Speech-to-Text API
    2. AssemblyAI
    3. Deepgram
    4. AWS Transcribe
    5. Microsoft Azure Cognitive Services Speech
    6. OpenAI Whisper (openai/whisper)

    AI recommended 6 alternatives but never named davabase/whisper_real_time. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 davabase/whisper_real_time?
    pass
    AI did not name davabase/whisper_real_time — 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 davabase/whisper_real_time in production, what risks or prerequisites should they evaluate first?
    pass
    AI named davabase/whisper_real_time 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 davabase/whisper_real_time solve, and who is the primary audience?
    pass
    AI named davabase/whisper_real_time explicitly

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

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davabase/whisper_real_time — 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