RRepoGEO

REPOGEO REPORT · LITE

wenet-e2e/wespeaker

Default branch master · commit 9ce79956 · scanned 5/25/2026, 10:01:47 PM

GitHub: 1,307 stars · 195 forks

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 wenet-e2e/wespeaker, 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 highlight production-readiness and toolkit nature

    Why:

    CURRENT
    WeSpeaker mainly focuses on **speaker embedding learning**, with application to the speaker verification task. We support online feature extraction or loading pre-extracted features in kaldi-format.
    COPY-PASTE FIX
    WeSpeaker is a research and production-oriented toolkit for robust speaker verification, recognition, and diarization. It focuses on advanced speaker embedding learning, providing a comprehensive, ready-to-deploy solution for speech technology applications.
  • mediumhomepage#2
    Add a project homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/wenet-e2e/wespeaker
  • lowreadme#3
    Emphasize WeNet ecosystem integration in README

    Why:

    COPY-PASTE FIX
    As part of the WeNet end-to-end speech processing ecosystem, WeSpeaker offers seamless integration and shared infrastructure for comprehensive speech applications.

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 wenet-e2e/wespeaker
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA Riva
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA Riva · recommended 1×
  2. Google Cloud Speech-to-Text API · recommended 1×
  3. Amazon Transcribe · recommended 1×
  4. Microsoft Azure Cognitive Services - Speech · recommended 1×
  5. pyannote/pyannote-audio · recommended 1×
  • CATEGORY QUERY
    How can I implement robust speaker verification and diarization in a production environment?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Riva
    2. Google Cloud Speech-to-Text API
    3. Amazon Transcribe
    4. Microsoft Azure Cognitive Services - Speech
    5. pyannote.audio (pyannote/pyannote-audio)
    6. SpeechBrain (speechbrain/speechbrain)
    7. Kaldi (kaldi-asr/kaldi)

    AI recommended 7 alternatives but never named wenet-e2e/wespeaker. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools are available for extracting speaker embeddings from audio for similarity tasks?
    you: not recommended
    AI recommended (in order):
    1. SpeechBrain
    2. pyannote.audio
    3. NVIDIA NeMo
    4. OpenVINO Toolkit
    5. Kaldi
    6. TensorFlow
    7. PyTorch

    AI recommended 7 alternatives but never named wenet-e2e/wespeaker. 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 wenet-e2e/wespeaker?
    pass
    AI did not name wenet-e2e/wespeaker — 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 wenet-e2e/wespeaker in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wenet-e2e/wespeaker 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 wenet-e2e/wespeaker solve, and who is the primary audience?
    pass
    AI named wenet-e2e/wespeaker explicitly

    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 wenet-e2e/wespeaker. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/wenet-e2e/wespeaker.svg)](https://repogeo.com/en/r/wenet-e2e/wespeaker)
HTML
<a href="https://repogeo.com/en/r/wenet-e2e/wespeaker"><img src="https://repogeo.com/badge/wenet-e2e/wespeaker.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

wenet-e2e/wespeaker — 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