RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/SONAR

Default branch main · commit 3a95f405 · scanned 6/4/2026, 4:07:08 AM

GitHub: 893 stars · 100 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 facebookresearch/SONAR, 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
    Add relevant topics to improve categorization and searchability

    Why:

    COPY-PASTE FIX
    multilingual, multimodal, sentence-embeddings, speech-processing, natural-language-processing, machine-translation, cross-modal, ai, deep-learning, facebook-ai
  • highreadme#2
    Reposition the README's opening to clearly state SONAR's core function and audience

    Why:

    CURRENT
    We introduce SONAR, a new multilingual and multimodal fixed-size sentence embedding space, with a full suite of speech and text encoders and decoders. It substantially outperforms existing sentence embeddings such as LASER3 and LabSE on the xsim and xsim++ multilingual similarity search tasks.
    COPY-PASTE FIX
    SONAR provides a new multilingual and multimodal fixed-size sentence embedding space, complete with speech and text encoders and decoders. Designed for researchers and developers, SONAR enables advanced applications like cross-modal similarity search and zero-shot speech-to-text translation, outperforming existing sentence embeddings such as LASER3 and LabSE.
  • mediumhomepage#3
    Add the research paper URL as the project homepage

    Why:

    COPY-PASTE FIX
    https://ai.meta.com/research/publications/sonar-sentence-level-multimodal-and-language-agnostic-representations/

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 facebookresearch/SONAR
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. OpenAI CLIP · recommended 1×
  3. Laion-AI CLAP · recommended 1×
  4. Google Universal Sentence Encoder · recommended 1×
  5. Sentence-BERT · recommended 1×
  • CATEGORY QUERY
    How to get fixed-size, language-agnostic sentence embeddings for text and speech similarity?
    you: not recommended
    AI recommended (in order):
    1. OpenAI CLIP
    2. Laion-AI CLAP
    3. Google Universal Sentence Encoder
    4. Sentence-BERT
    5. XLM-RoBERTa
    6. Wav2Vec 2.0
    7. HuBERT
    8. OpenAI Whisper

    AI recommended 8 alternatives but never named facebookresearch/SONAR. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a tool for cross-modal text and speech translation and embedding generation.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Translation AI
    2. Google Cloud Speech-to-Text
    3. Google Cloud Text-to-Speech
    4. AWS Translate
    5. AWS Transcribe
    6. AWS Polly
    7. Azure AI Translator
    8. Azure AI Speech
    9. Hugging Face Transformers
    10. Meta's SeamlessM4T
    11. Google's M4T
    12. OpenAI Whisper
    13. DeepL API
    14. OpenAI API
    15. GPT models
    16. ElevenLabs API

    AI recommended 16 alternatives but never named facebookresearch/SONAR. 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 facebookresearch/SONAR?
    pass
    AI named facebookresearch/SONAR explicitly

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

  • If a team adopts facebookresearch/SONAR in production, what risks or prerequisites should they evaluate first?
    pass
    AI named facebookresearch/SONAR 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 facebookresearch/SONAR solve, and who is the primary audience?
    pass
    AI named facebookresearch/SONAR 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 facebookresearch/SONAR. 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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  • Brand-free category queries5 vs 2 in Lite
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