RRepoGEO

REPOGEO REPORT · LITE

declare-lab/MELD

Default branch master · commit e8cedf27 · scanned 6/21/2026, 8:10:00 PM

GitHub: 1,059 stars · 232 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 declare-lab/MELD, 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 the dataset download link and clarify the repo's official status

    Why:

    CURRENT
    The README's initial content immediately after the main title is a 'Note' section that promotes other projects and then lists the MELD download link among other 'fire' updates.
    COPY-PASTE FIX
    This is the official GitHub repository for the MELD (Multimodal EmotionLines Dataset), a widely used resource for emotion recognition in conversation research.

**Download the MELD Dataset:**
You can download the full MELD dataset directly from Hugging Face:
```https://huggingface.co/datasets/declare-lab/MELD```

## Updates
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://huggingface.co/datasets/declare-lab/MELD
  • lowreadme#3
    Reorganize the 'Note' section to prioritize MELD-specific information

    Why:

    CURRENT
    The 'Note' section appears immediately after the main title, listing other projects before the MELD download link.
    COPY-PASTE FIX
    Move the cross-promotional links (AlgoPuzzleVQA, MM-Align, conv-emotion) to a new section further down the README, perhaps titled 'Related Projects' or 'Other Work from declare-lab', after the core MELD dataset information, leaderboard, and updates.

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 declare-lab/MELD
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
IEMOCAP (Interactive Emotional Dyadic Motion Capture) Dataset
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. IEMOCAP (Interactive Emotional Dyadic Motion Capture) Dataset · recommended 1×
  2. MSP-IMPROV (Multi-modal Spontaneous Speech Corpus for Emotion Recognition in Human-Computer Interaction) · recommended 1×
  3. MELD (Multi-modal EmotionLines Dataset) · recommended 1×
  4. DailyDialog · recommended 1×
  5. EmoContext (from SemEval-2019 Task 3) · recommended 1×
  • CATEGORY QUERY
    Where can I find a dataset for training AI to recognize emotions in multi-party dialogues?
    you: not recommended
    AI recommended (in order):
    1. IEMOCAP (Interactive Emotional Dyadic Motion Capture) Dataset
    2. MSP-IMPROV (Multi-modal Spontaneous Speech Corpus for Emotion Recognition in Human-Computer Interaction)
    3. MELD (Multi-modal EmotionLines Dataset)
    4. DailyDialog
    5. EmoContext (from SemEval-2019 Task 3)
    6. CMU-MOSEI (CMU Multimodal Opinion Sentiment and Emotion Intensity)

    AI recommended 6 alternatives but never named declare-lab/MELD. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What resources exist for multimodal sentiment analysis and emotion detection in conversational AI?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. OpenSMILE
    3. Librosa
    4. SpeechBrain
    5. TensorFlow
    6. PyTorch
    7. VADER
    8. Flair

    AI recommended 8 alternatives but never named declare-lab/MELD. 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 declare-lab/MELD?
    pass
    AI named declare-lab/MELD explicitly

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

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

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

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declare-lab/MELD — 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