RRepoGEO

REPOGEO REPORT · LITE

FireRedTeam/FireRedASR

Default branch main · commit 834635e4 · scanned 5/16/2026, 7:08:18 AM

GitHub: 1,883 stars · 161 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 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
  • highabout#1
    Clarify "ASR" in the repository description

    Why:

    CURRENT
    Open-source industrial-grade ASR models supporting Mandarin, Chinese dialects and English, achieving a new SOTA on public Mandarin ASR benchmarks, while also offering outstanding singing lyrics recognition capability.
    COPY-PASTE FIX
    FireRedASR: Open-source industrial-grade **Automatic Speech Recognition (ASR)** models supporting Mandarin, Chinese dialects and English, achieving new SOTA on public Mandarin ASR benchmarks, while also offering outstanding singing lyrics recognition capability.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://fireredteam.github.io/demos/firered_asr/
  • mediumreadme#3
    Reorder README introduction to highlight FireRedASR's core features

    Why:

    CURRENT
    **FireRedASR2S has been open-sourced! Welcome to try it! https://github.com/FireRedTeam/FireRedASR2SFireRedASR2S is a state-of-the-art (SOTA), industrial-grade, all-in-one ASR system with ASR, VAD, LID, and Punc modules. All modules achieve SOTA performance.**

FireRedASR is a family of open-source industrial-grade automatic speech recognition (ASR) models supporting Mandarin, Chinese dialects and English, achieving a new state-of-the-art (SOTA) on public Mandarin ASR benchmarks, while also offering outstanding singing lyrics recognition capability.
    COPY-PASTE FIX
    FireRedASR is a family of open-source industrial-grade automatic speech recognition (ASR) models supporting Mandarin, Chinese dialects and English, achieving a new state-of-the-art (SOTA) on public Mandarin ASR benchmarks, while also offering outstanding singing lyrics recognition capability.

**🔥 News: FireRedASR2S has been open-sourced! Welcome to try it!** FireRedASR2S is a state-of-the-art (SOTA), industrial-grade, all-in-one ASR system with ASR, VAD, LID, and Punc modules. All modules achieve SOTA performance. See https://github.com/FireRedTeam/FireRedASR2S

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. facebookresearch/fairseq · recommended 1×
  3. Conformer · recommended 1×
  4. espnet/espnet · recommended 1×
  5. NVIDIA/NeMo · recommended 1×
  • CATEGORY QUERY
    What are the best open-source automatic speech recognition models for Mandarin and English?
    you: not recommended
    AI recommended (in order):
    1. Whisper (openai/whisper)
    2. Wav2Vec 2.0 (facebookresearch/fairseq)
    3. Conformer
    4. ESPnet (espnet/espnet)
    5. NeMo (NVIDIA/NeMo)
    6. DeepSpeech (mozilla/DeepSpeech)
    7. Kaldi (kaldi-asr/kaldi)

    AI recommended 7 alternatives but never named FireRedTeam/FireRedASR. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an industrial-grade ASR system with state-of-the-art performance for Chinese dialects and singing lyrics.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Speech-to-Text
    2. Microsoft Azure Cognitive Services Speech
    3. Baidu AI Cloud Speech
    4. Alibaba Cloud Intelligent Speech Interaction
    5. AWS Transcribe
    6. Deepgram
    7. OpenAI Whisper

    AI recommended 7 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

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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