RRepoGEO

REPOGEO REPORT · LITE

yl4579/StyleTTS2

Default branch main · commit 5cedc71c · scanned 6/20/2026, 10:17:21 AM

GitHub: 6,291 stars · 691 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)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 yl4579/StyleTTS2, 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
  • highhomepage#1
    Add project homepage URL to repository About section

    Why:

    COPY-PASTE FIX
    https://styletts2.github.io/
  • highreadme#2
    Add a concise, project-oriented opening sentence to the README

    Why:

    COPY-PASTE FIX
    StyleTTS 2 is an open-source text-to-speech (TTS) model that achieves human-level speech synthesis through style diffusion and adversarial training, designed for researchers and developers.
  • mediumreadme#3
    Add a 'Key Features' or 'Why StyleTTS2?' section to highlight differentiators

    Why:

    COPY-PASTE FIX
    ### Key Features

*   **Human-Level Naturalness:** Achieves state-of-the-art speech quality, surpassing human recordings on LJSpeech and matching on VCTK.
*   **Flexible Style Generation:** Leverages style diffusion models to generate suitable styles without reference speech, offering diverse and controllable synthesis.
*   **Zero-Shot Speaker Adaptation:** Outperforms previous models for adapting to new speakers with no prior training data.
*   **End-to-End Training:** Utilizes large pre-trained speech language models (SLMs) like WavLM as discriminators for improved naturalness.

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 yl4579/StyleTTS2
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Text-to-Speech · recommended 1×
  2. ElevenLabs Prime Voice AI · recommended 1×
  3. Microsoft Azure AI Speech · recommended 1×
  4. Amazon Polly · recommended 1×
  5. Meta Voicebox · recommended 1×
  • CATEGORY QUERY
    How can I generate highly natural and expressive speech from text using deep learning?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Text-to-Speech
    2. ElevenLabs Prime Voice AI
    3. Microsoft Azure AI Speech
    4. Amazon Polly
    5. Meta Voicebox
    6. OpenAI TTS
    7. Coqui TTS (https://github.com/coqui-ai/TTS)

    AI recommended 7 alternatives but never named yl4579/StyleTTS2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source models provide human-like text-to-speech with flexible style generation?
    you: not recommended
    AI recommended (in order):
    1. VITS
    2. Tacotron 2
    3. WaveGlow
    4. Hifi-GAN
    5. ESPnet
    6. FastSpeech 2
    7. FastSpeech 2s
    8. Coqui TTS

    AI recommended 8 alternatives but never named yl4579/StyleTTS2. 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 yl4579/StyleTTS2?
    pass
    AI named yl4579/StyleTTS2 explicitly

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

  • If a team adopts yl4579/StyleTTS2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yl4579/StyleTTS2 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 yl4579/StyleTTS2 solve, and who is the primary audience?
    pass
    AI named yl4579/StyleTTS2 explicitly

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

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yl4579/StyleTTS2 — 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