RRepoGEO

REPOGEO REPORT · LITE

antirez/qwen-asr

Default branch main · commit b00b789b · scanned 6/11/2026, 5:32:50 PM

GitHub: 562 stars · 65 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 antirez/qwen-asr, 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 the repository

    Why:

    COPY-PASTE FIX
    speech-to-text, asr, speech-recognition, c-library, qwen-asr, inference, low-dependency, real-time
  • mediumabout#2
    Update the repository description for clarity

    Why:

    CURRENT
    C inference for Qwen3-ASR 0.6b and 1.7b transcriptions models
    COPY-PASTE FIX
    Pure C inference library for Qwen3-ASR 0.6b and 1.7b speech-to-text models, optimized for low-dependency server-side transcription.
  • mediumreadme#3
    Refine the README's opening sentence to emphasize library function

    Why:

    CURRENT
    This is a C implementation of the inference pipeline for Qwen3-ASR speech-to-text models (both 0.6B and 1.7B).
    COPY-PASTE FIX
    This is a pure C, zero-dependency library for Qwen3-ASR speech-to-text models (0.6B and 1.7B), providing fast, server-side transcription.

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 antirez/qwen-asr
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
alphacep/vosk-api
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. alphacep/vosk-api · recommended 1×
  2. mozilla/DeepSpeech · recommended 1×
  3. Picovoice Rhino · recommended 1×
  4. kaldi-asr/kaldi · recommended 1×
  5. Google Cloud Speech-to-Text API · recommended 1×
  • CATEGORY QUERY
    Looking for an efficient, low-dependency speech-to-text library for server-side C applications.
    you: not recommended
    AI recommended (in order):
    1. Vosk API (alphacep/vosk-api)
    2. Mozilla DeepSpeech (mozilla/DeepSpeech)
    3. Picovoice Rhino
    4. Kaldi (kaldi-asr/kaldi)
    5. Google Cloud Speech-to-Text API

    AI recommended 5 alternatives but never named antirez/qwen-asr. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a lightweight, pure C speech recognition library with minimal external dependencies.
    you: not recommended
    AI recommended (in order):
    1. Vosk API
    2. Picovoice Porcupine
    3. Rhino
    4. Mozilla DeepSpeech
    5. Pocketsphinx
    6. Kaldi

    AI recommended 6 alternatives but never named antirez/qwen-asr. 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 antirez/qwen-asr?
    pass
    AI named antirez/qwen-asr explicitly

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

  • If a team adopts antirez/qwen-asr in production, what risks or prerequisites should they evaluate first?
    pass
    AI named antirez/qwen-asr 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 antirez/qwen-asr solve, and who is the primary audience?
    pass
    AI named antirez/qwen-asr explicitly

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

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antirez/qwen-asr — 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