RRepoGEO

REPOGEO REPORT · LITE

YuanGongND/ast

Default branch master · commit 31088be8 · scanned 5/22/2026, 3:34:08 PM

GitHub: 1,458 stars · 245 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)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
54 /100
Needs work
Category recall
1 / 2
Avg rank #6.0 when recommended
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 YuanGongND/ast, 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
    Update 'About' description to clarify project domain and use cases

    Why:

    CURRENT
    Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".
    COPY-PASTE FIX
    Official PyTorch implementation of the Audio Spectrogram Transformer (AST) for audio event classification, speech recognition, and keyword spotting. This repository provides code and pretrained models from the Interspeech 2021 paper.
  • highreadme#2
    Add a clear introductory sentence to README

    Why:

    COPY-PASTE FIX
    (Insert this right after the H1) "This repository provides the official PyTorch implementation for the Audio Spectrogram Transformer (AST), a deep learning model designed for various audio tasks including audio event classification, speech recognition, and keyword spotting."
  • mediumhomepage#3
    Add project homepage link to 'About' section

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2104.01778

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
1 / 2
50% of queries surface YuanGongND/ast
Avg rank
#6.0
Lower is better. #1 = top recommendation.
Share of voice
9%
Of all named tools, what % are you?
Top rival
ResNet
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ResNet · recommended 1×
  2. VGG · recommended 1×
  3. EfficientNet · recommended 1×
  4. MobileNetV2/V3 · recommended 1×
  5. PANNs · recommended 1×
  • CATEGORY QUERY
    What deep learning models are effective for audio event classification using spectrograms?
    you: #6
    AI recommended (in order):
    1. ResNet
    2. VGG
    3. EfficientNet
    4. MobileNetV2/V3
    5. PANNs
    6. AST ← you
    Show full AI answer
  • CATEGORY QUERY
    Seeking a PyTorch framework for speech command recognition and keyword spotting.
    you: not recommended
    AI recommended (in order):
    1. SpeechBrain (speechbrain/speechbrain)
    2. PyTorch-Kaldi (mravanelli/pytorch-kaldi)
    3. torchaudio (pytorch/audio)
    4. Hugging Face Transformers (huggingface/transformers)
    5. KWS-LC

    AI recommended 5 alternatives but never named YuanGongND/ast. 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 YuanGongND/ast?
    pass
    AI named YuanGongND/ast explicitly

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

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

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

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MARKDOWN (README)
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YuanGongND/ast — 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
YuanGongND/ast — RepoGEO report