RRepoGEO

REPOGEO REPORT · LITE

TEN-framework/ten-vad

Default branch main · commit 22a3bcd4 · scanned 5/14/2026, 3:27:24 PM

GitHub: 2,115 stars · 168 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 TEN-framework/ten-vad, 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
    Add a concise, keyword-rich value proposition to the README's opening

    Why:

    CURRENT
    The current README starts with badges and 'Latest News'.
    COPY-PASTE FIX
    TEN-framework/ten-vad is a **low-latency, high-performance, and lightweight Voice Activity Detector (VAD)** designed for real-time audio processing. It offers broad cross-platform support, including **Python, WebAssembly (WASM), Golang, Java, and Android**, making it ideal for speech applications, conversational AI, and voice command systems where efficiency and accuracy are paramount. Integrated into projects like `k2-fsa/sherpa-onnx`, TEN-VAD provides robust speech segment extraction for enhanced ASR experiences.
  • mediumreadme#2
    Add a 'Why TEN-VAD?' or 'Key Differentiators' section to the README

    Why:

    COPY-PASTE FIX
    ## Why TEN-VAD?
TEN-framework/ten-vad stands out due to its exceptional low-latency performance, broad cross-platform support (WASM, Python, Go, Java, Android), and seamless integration with projects like `k2-fsa/sherpa-onnx`. Unlike many alternatives, it focuses on a minimal resource footprint while maintaining high accuracy, making it ideal for embedded and real-time applications.
  • mediumreadme#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    TEN-framework/ten-vad is licensed under [Specify License Name(s) here, e.g., 'a custom license, see LICENSE file for details.'].

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 TEN-framework/ten-vad
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
WebRTC VAD
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. WebRTC VAD · recommended 1×
  2. Silero VAD · recommended 1×
  3. Vosk VAD · recommended 1×
  4. OpenVAD · recommended 1×
  5. pyannote.audio · recommended 1×
  • CATEGORY QUERY
    What are some low-latency, high-performance voice activity detection libraries for real-time audio?
    you: not recommended
    AI recommended (in order):
    1. WebRTC VAD
    2. Silero VAD
    3. Vosk VAD
    4. OpenVAD
    5. pyannote.audio

    AI recommended 5 alternatives but never named TEN-framework/ten-vad. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a lightweight voice activity detector with Python and WebAssembly support for speech applications.
    you: not recommended
    AI recommended (in order):
    1. VAD.js
    2. Silero VAD (snakers4/silero-vad)
    3. Picovoice Porcupine (Picovoice/porcupine)
    4. Mozilla DeepSpeech VAD (mozilla/DeepSpeech)
    5. webrtcvad (wiseman/py-webrtcvad)

    AI recommended 5 alternatives but never named TEN-framework/ten-vad. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 TEN-framework/ten-vad?
    pass
    AI did not name TEN-framework/ten-vad — 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 TEN-framework/ten-vad in production, what risks or prerequisites should they evaluate first?
    pass
    AI named TEN-framework/ten-vad 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 TEN-framework/ten-vad solve, and who is the primary audience?
    pass
    AI named TEN-framework/ten-vad explicitly

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

Embed your GEO score

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MARKDOWN (README)
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HTML
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TEN-framework/ten-vad — 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