ustwo-api / data /meld_test /README.md
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MELD English Test Sets

Emotion Label Alignment

UsTwo Pipeline (EN) MELD Label Match
neutral neutral βœ… Exact
joy joy βœ… Exact
sadness sadness βœ… Exact
anger anger βœ… Exact
surprise surprise βœ… Exact
fear fear βœ… Exact
disgust disgust βœ… Exact

7/7 labels match exactly. No mapping needed.

Test Sets

File Scenario Speakers Primary Emotion Duration Utterances Emotion Distribution
01_angry_fight Couple in a heated argument Ross, Rachel anger 36.9s 11 utts anger:7 neutral:2 sadness:1 disgust:1
02_happy_loving Couple being affectionate and playful Chandler, Monica joy 43.8s 16 utts joy:6 surprise:5 anger:3 neutral:1 sadness:1
03_sad_emotional Emotional confession β€” "you still love me?" Ross, Rachel sadness 55.4s 17 utts neutral:7 sadness:4 anger:3 surprise:3
04_surprise_shock Drunk voicemail surprise scene Ross, Rachel surprise 30.2s 8 utts surprise:5 neutral:2 sadness:1
05_fear_anxiety Anxious and worried conversation Chandler, Rachel fear 19.9s 12 utts fear:5 neutral:4 surprise:2 sadness:1
06_disgust_annoyance Annoyed and frustrated bickering Joey, Rachel anger 29.2s 11 utts anger:5 neutral:2 sadness:1 surprise:1 fear:1 joy:1
07_bittersweet Saying goodbye with conflicting feelings Ross, Rachel sadness 43.3s 14 utts sadness:6 surprise:3 anger:3 fear:1 neutral:1
08_calm_daily Casual everyday chitchat (baseline) Joey, Monica neutral 40.4s 15 utts neutral:13 joy:2
09_opposite_emotions Tense speaker + calm listener β€” triggers listening pair animation 2 spk surprise 24.9s 11 segs surprise:5 neutral:3 anger:1 fear:1 joy:1 (pipeline fused)

Notes

  • All dialogues are 2-speaker (male + female) conversations
  • 03: Ross+Rachel only, utt15 removed (timestamp overlap with utt14)
  • 04: starts from "Rach, I got a message from you", utt3/utt8 removed (timestamp overlaps)
  • 06: Joey+Rachel only, utt16 removed (addresses Ross)
  • 07: utt11 removed (timestamp overlap with utt10)
  • 09: opposite-emotion demo scene (updated 2026-04-22) β€” WAV replaced by user. E2E pipeline output: speaker_0 dominant=surprise (max 0.68, tense via anger residual), speaker_1 dominant=neutral (max 0.54, calm). (tense, calm) β†’ pair_state=listening triggers (sparkles effect, speaker_1 = giver/listener). Recap captures "one expressing worry through sharp words, the other sharing tender vision." Per-utterance ground-truth labels not available post-update; distribution numbers derived from pipeline fused output.

Source

  • Dataset: MELD (Multimodal EmotionLines Dataset)
  • Source: Friends TV series
  • Paper: Poria et al., ACL 2019
  • Each WAV is a full dialogue concatenated from per-utterance MP4 clips
  • Audio: 16kHz mono PCM (matches pipeline input format)

Usage

# Run pipeline on a single test set
python scripts/run_pipeline.py data/meld_test/01_angry_fight.wav

# Evaluate all test sets
python scripts/evaluate_meld_test.py