RRepoGEO

REPOGEO REPORT · LITE

HumeAI/tada

Default branch main · commit d6b72c33 · scanned 6/3/2026, 12:53:04 PM

GitHub: 986 stars · 107 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 HumeAI/tada, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Refine the repository description for clarity

    Why:

    CURRENT
    Open Source Speech Language Model
    COPY-PASTE FIX
    Open Source Generative Speech Language Model for high-fidelity Text-to-Speech and Speech Synthesis.
  • mediumlicense#2
    Clarify the license in the README

    Why:

    COPY-PASTE FIX
    This project is licensed under the terms found in the [LICENSE file](LICENSE). Please review the file for specific details regarding usage and distribution.

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 HumeAI/tada
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Text-to-Speech
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Text-to-Speech · recommended 2×
  2. Amazon Polly · recommended 2×
  3. ElevenLabs · recommended 2×
  4. Microsoft Azure Cognitive Services Speech · recommended 1×
  5. VITS · recommended 1×
  • CATEGORY QUERY
    How can I generate high-fidelity, natural-sounding speech from text with reduced computational cost?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Text-to-Speech
    2. Amazon Polly
    3. Microsoft Azure Cognitive Services Speech
    4. VITS
    5. Coqui TTS
    6. Bark
    7. ElevenLabs

    AI recommended 7 alternatives but never named HumeAI/tada. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a generative speech model that synchronizes text and audio to prevent hallucination.
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs
    2. Google Cloud Text-to-Speech
    3. Microsoft Azure AI Speech
    4. Amazon Polly
    5. Meta's Voicebox

    AI recommended 5 alternatives but never named HumeAI/tada. 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 HumeAI/tada?
    pass
    AI named HumeAI/tada explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite