RRepoGEO

REPOGEO REPORT · LITE

FireRedTeam/FireRedASR

Default branch main · commit 834635e4 · scanned 6/27/2026, 2:38:03 AM

GitHub: 1,912 stars · 163 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)

3 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 FireRedTeam/FireRedASR, 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
    Explicitly disambiguate 'ASR' in the README

    Why:

    COPY-PASTE FIX
    Add a clear disambiguation statement early in the README, for example, right after the initial project description: "Please note: ASR in FireRedASR stands for **Automatic Speech Recognition**, not Attack Surface Reduction. This project focuses on converting spoken language into text."
  • highhomepage#2
    Add a Homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://fireredteam.github.io/demos/firered_asr/
  • mediumtopics#3
    Enhance topics with specific use cases and languages

    Why:

    CURRENT
    asr, automatic-speech-recognition, conformer, industrial-grade, llm, multimodal-llm, open-source, speech-recognition, speechllm, transformer
    COPY-PASTE FIX
    asr, automatic-speech-recognition, conformer, industrial-grade, llm, multimodal-llm, open-source, speech-recognition, speechllm, transformer, mandarin-asr, chinese-asr, singing-lyrics-recognition, speech-to-text

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 FireRedTeam/FireRedASR
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. openai/whisper · recommended 1×
  2. wenet-e2e/wenet · recommended 1×
  3. alibaba/FunASR · recommended 1×
  4. espnet/espnet · recommended 1×
  5. NVIDIA/NeMo · recommended 1×
  • CATEGORY QUERY
    Which open-source ASR systems provide state-of-the-art performance for Mandarin speech?
    you: not recommended
    AI recommended (in order):
    1. Whisper (openai/whisper)
    2. WeNet (wenet-e2e/wenet)
    3. FunASR (alibaba/FunASR)
    4. ESPnet (espnet/espnet)
    5. NeMo (NVIDIA/NeMo)
    6. Kaldi (kaldi-asr/kaldi)

    AI recommended 6 alternatives but never named FireRedTeam/FireRedASR. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I accurately transcribe singing vocals and spoken dialogue using an open-source tool?
    you: not recommended
    AI recommended (in order):
    1. Whisper
    2. Mozilla DeepSpeech
    3. Kaldi
    4. Vosk

    AI recommended 4 alternatives but never named FireRedTeam/FireRedASR. 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 FireRedTeam/FireRedASR?
    pass
    AI named FireRedTeam/FireRedASR explicitly

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

  • If a team adopts FireRedTeam/FireRedASR in production, what risks or prerequisites should they evaluate first?
    pass
    AI named FireRedTeam/FireRedASR 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 FireRedTeam/FireRedASR solve, and who is the primary audience?
    pass
    AI named FireRedTeam/FireRedASR 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 FireRedTeam/FireRedASR. 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
<a href="https://repogeo.com/en/r/FireRedTeam/FireRedASR"><img src="https://repogeo.com/badge/FireRedTeam/FireRedASR.svg" alt="RepoGEO" /></a>
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FireRedTeam/FireRedASR — 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