RRepoGEO

REPOGEO REPORT · LITE

fossasia/susi_translator

Default branch main · commit d68f046c · scanned 5/15/2026, 4:42:46 AM

GitHub: 1,004 stars · 26 forks

AI VISIBILITY SCORE
28 /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
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 fossasia/susi_translator, 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 opening to clarify project type and purpose

    Why:

    CURRENT
    # SUSI Translator

Real-time audio transcription + optional translation prototype with:
    COPY-PASTE FIX
    # SUSI Translator: Self-Hostable Real-time Audio Transcription & Translation API (Python/Django/Flask)

This repository provides an open-source, self-hostable prototype for real-time audio transcription and optional translation. It features a Python API backend (Django or Flask) and client examples, designed for developers looking to build custom speech-to-text and translation services.
  • hightopics#2
    Add relevant GitHub topics

    Why:

    COPY-PASTE FIX
    python, django, flask, speech-to-text, audio-transcription, real-time, translation, api, self-hosted, open-source, machine-learning
  • mediumreadme#3
    Add a 'Project Status' section to the README

    Why:

    COPY-PASTE FIX
    ## Project Status

This project is a prototype last updated in 2018. While functional, it is not actively maintained and may require updates for modern environments or dependencies. It serves as a valuable reference for building real-time audio transcription and translation services.

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 fossasia/susi_translator
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Speech-to-Text API
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Speech-to-Text API · recommended 2×
  2. Google Cloud Translation API · recommended 2×
  3. AssemblyAI · recommended 2×
  4. Amazon Transcribe · recommended 1×
  5. Amazon Translate · recommended 1×
  • CATEGORY QUERY
    How to build a real-time audio transcription and translation service with Python?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Speech-to-Text API
    2. Google Cloud Translation API
    3. Amazon Transcribe
    4. Amazon Translate
    5. Boto3
    6. Azure Speech-to-Text
    7. Azure Translator
    8. OpenAI Whisper
    9. DeepL API
    10. PyAudio
    11. sounddevice
    12. AssemblyAI
    13. asyncio

    AI recommended 13 alternatives but never named fossasia/susi_translator. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python API backend for real-time speech-to-text and language translation.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Speech-to-Text API
    2. Google Cloud Translation API
    3. AWS Transcribe
    4. AWS Translate
    5. Azure Speech Service
    6. Translator Text API
    7. Deepgram
    8. AssemblyAI
    9. OpenAI Whisper (openai/whisper)
    10. Hugging Face Transformers (huggingface/transformers)

    AI recommended 10 alternatives but never named fossasia/susi_translator. 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 fossasia/susi_translator?
    pass
    AI did not name fossasia/susi_translator — 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 fossasia/susi_translator in production, what risks or prerequisites should they evaluate first?
    pass
    AI named fossasia/susi_translator 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 fossasia/susi_translator solve, and who is the primary audience?
    pass
    AI named fossasia/susi_translator 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 fossasia/susi_translator. 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
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fossasia/susi_translator — 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