RRepoGEO

REPOGEO REPORT · LITE

lturing/tacotronv2_wavernn_chinese

Default branch master · commit 399a5d9f · scanned 6/15/2026, 1:13:04 AM

GitHub: 535 stars · 132 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 lturing/tacotronv2_wavernn_chinese, 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
  • highlicense#1
    Add a LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT License) in the repository root to clearly state the terms of use.
  • mediumreadme#2
    Reposition the README H1 to emphasize Chinese TTS

    Why:

    CURRENT
    # TacotronV2 + WaveRNN
    COPY-PASTE FIX
    # High-Quality Chinese Speech Synthesis (TTS) with TacotronV2 + WaveRNN

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 lturing/tacotronv2_wavernn_chinese
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ESPnet
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ESPnet · recommended 2×
  2. PaddleSpeech · recommended 2×
  3. Coqui TTS · recommended 2×
  4. TensorFlowTTS · recommended 2×
  5. VITS · recommended 1×
  • CATEGORY QUERY
    How to implement a high-quality deep learning text-to-speech system for Chinese language?
    you: not recommended
    AI recommended (in order):
    1. ESPnet
    2. PaddleSpeech
    3. Coqui TTS
    4. TensorFlowTTS
    5. VITS
    6. FastSpeech2
    7. pypinyin
    8. jieba

    AI recommended 8 alternatives but never named lturing/tacotronv2_wavernn_chinese. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for open-source deep learning models to generate natural Chinese speech with speaker adaptation.
    you: not recommended
    AI recommended (in order):
    1. ESPnet
    2. PaddleSpeech
    3. Coqui TTS
    4. OpenVITS
    5. TensorFlowTTS
    6. Mozilla TTS

    AI recommended 6 alternatives but never named lturing/tacotronv2_wavernn_chinese. 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 lturing/tacotronv2_wavernn_chinese?
    pass
    AI named lturing/tacotronv2_wavernn_chinese explicitly

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

  • If a team adopts lturing/tacotronv2_wavernn_chinese in production, what risks or prerequisites should they evaluate first?
    pass
    AI named lturing/tacotronv2_wavernn_chinese 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 lturing/tacotronv2_wavernn_chinese solve, and who is the primary audience?
    pass
    AI did not name lturing/tacotronv2_wavernn_chinese — 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

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lturing/tacotronv2_wavernn_chinese — 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