RRepoGEO

REPOGEO REPORT · LITE

ming024/FastSpeech2

Default branch master · commit d4e79eb5 · scanned 5/25/2026, 6:27:28 AM

GitHub: 2,174 stars · 613 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 ming024/FastSpeech2, 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
  • highreadme#1
    Clarify the README's opening to emphasize its nature as a research implementation

    Why:

    CURRENT
    # FastSpeech 2 - PyTorch Implementation

This is a PyTorch implementation of Microsoft's text-to-speech system **FastSpeech 2: Fast and High-Quality End-to-End Text to Speech**.
    COPY-PASTE FIX
    # FastSpeech 2 - PyTorch Implementation

This repository provides a PyTorch implementation of Microsoft's research paper, **FastSpeech 2: Fast and High-Quality End-to-End Text to Speech**. It's designed for researchers and developers working on speech synthesis, offering a flexible codebase for experimentation and further development.
  • mediumhomepage#2
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://ming024.github.io/FastSpeech2/

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 ming024/FastSpeech2
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 Text to Speech · recommended 1×
  5. coqui-ai/TTS · recommended 1×
  • CATEGORY QUERY
    What are some fast and high-quality end-to-end text-to-speech systems available?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Text-to-Speech
    2. Amazon Polly
    3. Microsoft Azure Text to Speech
    4. ElevenLabs
    5. Coqui TTS (coqui-ai/TTS)
    6. Meta AI's Voicebox
    7. Mozilla TTS (mozilla/TTS)

    AI recommended 7 alternatives but never named ming024/FastSpeech2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a text-to-speech model supporting both English and Mandarin with multiple speakers.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Text-to-Speech
    2. Azure AI Speech
    3. Amazon Polly
    4. ElevenLabs
    5. Baidu AI Cloud Speech

    AI recommended 5 alternatives but never named ming024/FastSpeech2. 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 ming024/FastSpeech2?
    pass
    AI named ming024/FastSpeech2 explicitly

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

  • If a team adopts ming024/FastSpeech2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ming024/FastSpeech2 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 ming024/FastSpeech2 solve, and who is the primary audience?
    pass
    AI named ming024/FastSpeech2 explicitly

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

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ming024/FastSpeech2 — 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