RRepoGEO

REPOGEO REPORT · LITE

archinetai/audio-ai-timeline

Default branch main · commit 48956cc8 · scanned 6/25/2026, 3:18:01 PM

GitHub: 1,910 stars · 71 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
28 /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
2 / 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 archinetai/audio-ai-timeline, 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
    Refine README's opening sentence to emphasize 'curated timeline'

    Why:

    CURRENT
    Here we will keep track of the latest AI models for waveform based audio generation, starting in 2023!
    COPY-PASTE FIX
    This repository offers a **curated, chronological timeline** of significant advancements and milestones in Audio AI, specifically tracking the latest waveform-based audio generation models since 2023. It serves as a comprehensive resource for researchers, students, and enthusiasts to easily keep track of new developments.
  • highlicense#2
    Add a standard open-source LICENSE file

    Why:

    COPY-PASTE FIX
    Add a standard open-source LICENSE file (e.g., MIT, Apache-2.0) to the repository root.
  • mediumhomepage#3
    Set the repository's homepage URL

    Why:

    COPY-PASTE FIX
    Set the repository's homepage URL in the 'About' section to the live deployment of the Next.js application.

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 archinetai/audio-ai-timeline
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Papers With Code
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Papers With Code · recommended 2×
  2. Google AI Blog · recommended 2×
  3. Hugging Face Models · recommended 1×
  4. GitHub · recommended 1×
  5. DeepMind Blog · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of recent AI models for generating audio?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Models
    2. Papers With Code
    3. GitHub
    4. Google AI Blog
    5. DeepMind Blog
    6. Meta AI Blog
    7. arXiv
    8. The Batch by DeepLearning.AI
    9. SyncedReview
    10. VentureBeat AI
    11. Two Minute Papers
    12. Yannic Kilcher

    AI recommended 12 alternatives but never named archinetai/audio-ai-timeline. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I keep track of the latest advancements in AI for audio synthesis?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Hugging Face Blog
    3. Hugging Face Spaces
    4. Google AI Blog
    5. Papers With Code
    6. Twitter
    7. The Gradient
    8. NeurIPS
    9. ICML
    10. ICLR
    11. ISMIR
    12. INTERSPEECH
    13. WASPAA

    AI recommended 13 alternatives but never named archinetai/audio-ai-timeline. 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 archinetai/audio-ai-timeline?
    pass
    AI named archinetai/audio-ai-timeline explicitly

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

  • If a team adopts archinetai/audio-ai-timeline in production, what risks or prerequisites should they evaluate first?
    pass
    AI named archinetai/audio-ai-timeline 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 archinetai/audio-ai-timeline solve, and who is the primary audience?
    pass
    AI did not name archinetai/audio-ai-timeline — 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?

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archinetai/audio-ai-timeline — 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