RRepoGEO

REPOGEO REPORT · LITE

DmitryRyumin/ICASSP-2023-24-Papers

Default branch main · commit b1502c2e · scanned 6/12/2026, 5:17:35 AM

GitHub: 527 stars · 23 forks

AI VISIBILITY SCORE
15 /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
0 / 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 DmitryRyumin/ICASSP-2023-24-Papers, 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
    Reposition README opening to clarify repo's nature

    Why:

    COPY-PASTE FIX
    This repository offers a comprehensive, community-curated collection of research papers from ICASSP 2023 and 2024, frequently including direct links to their associated code implementations. It's designed as a centralized resource for the latest advancements in acoustics, speech, and signal processing.
  • mediumhomepage#2
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers
  • lowtopics#3
    Add a topic to describe the repository type

    Why:

    CURRENT
    asr, denoising, domain-adaptation, face-recognition, generative-models, icassp, icassp2023, icassp2024, image-generation, keyword-spotting, language-modeling, multimodal-learning, music-generation, self-supervised-learning, semantic-segmentation, signal-processing, signal-restoration, speech-recognition, spoken-language-understanding, vad
    COPY-PASTE FIX
    asr, denoising, domain-adaptation, face-recognition, generative-models, icassp, icassp2023, icassp2024, image-generation, keyword-spotting, language-modeling, multimodal-learning, music-generation, research-paper-collection, self-supervised-learning, semantic-segmentation, signal-processing, signal-restoration, speech-recognition, spoken-language-understanding, vad

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 DmitryRyumin/ICASSP-2023-24-Papers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv.org
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv.org · recommended 1×
  2. GitHub · recommended 1×
  3. Papers With Code · recommended 1×
  4. Google Scholar · recommended 1×
  5. Semantic Scholar · recommended 1×
  • CATEGORY QUERY
    Where can I find recent research papers and code for speech and signal processing?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. GitHub
    3. Papers With Code
    4. Google Scholar
    5. Semantic Scholar
    6. INTERSPEECH
    7. ICASSP
    8. NeurIPS
    9. ICML
    10. Hugging Face
    11. Transformers library
    12. IEEE Xplore

    AI recommended 12 alternatives but never named DmitryRyumin/ICASSP-2023-24-Papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for implementations of advanced multimodal learning or generative models in audio processing.
    you: not recommended
    AI recommended (in order):
    1. AudioGen
    2. MusicGen
    3. Riffusion
    4. Jukebox
    5. Whisper
    6. CLAP
    7. WaveNet

    AI recommended 7 alternatives but never named DmitryRyumin/ICASSP-2023-24-Papers. 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 DmitryRyumin/ICASSP-2023-24-Papers?
    pass
    AI did not name DmitryRyumin/ICASSP-2023-24-Papers — likely talking about a different project

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

  • If a team adopts DmitryRyumin/ICASSP-2023-24-Papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name DmitryRyumin/ICASSP-2023-24-Papers — likely talking about a different project

    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 DmitryRyumin/ICASSP-2023-24-Papers solve, and who is the primary audience?
    pass
    AI did not name DmitryRyumin/ICASSP-2023-24-Papers — likely talking about a different project

    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 DmitryRyumin/ICASSP-2023-24-Papers. 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite