TTS-AGI/enhanced-emo-snippets-balanced-DACVAE

Enhanced Emotion Snippets — Balanced DACVAE

A balanced, emotion-bucketed subset of TTS-AGI/enhanced-audiosnippets-DACVAE, organized by Empathic Insight Voice+ emotion and voice attribute categories.

Overview

This dataset provides up to 100 samples per magnitude bucket for each of the 40 emotion categories and 15 voice attribute dimensions scored by Empathic Insight Voice+.

Selection Criteria

Emotion Categories (40 dimensions)

For each emotion (e.g., Anger, Elation, Sadness, ...):

1. Dominant emotion filter: Only samples where this emotion has the highest value among all 40 emotion dimensions are included. This ensures each sample's characteristic emotion matches the category.
2. Magnitude bucketing: Samples are grouped into buckets of width 1 (e.g., [0,1), [1,2), [2,3), ...)
3. Quality ranking: Within each bucket, samples are ranked by score_speech_quality (descending)
4. Top 100: Up to 100 samples are selected per bucket

Voice Attributes (15 dimensions)

For each attribute (e.g., Age, Gender, Arousal, ...):

1. No dominant-emotion filter (these are orthogonal to emotion)
2. Same bucketing, ranking, and selection as above

Data Format

The dataset is in WebDataset format (.tar files), with one tar per category.

Each sample contains:

• {key}.json — Full metadata including:
  • sample_id, duration, caption, transcription
  • empathic_insight_scores (all 55 dimensions)
  • speaker_embedding (256-d)
  • emotion_vector, detailed_caption, bude_whisper_caption
  • _bucket_category, _bucket_value, _bucket_label
  • _is_dominant_emotion (whether dominant-emotion filter was applied)
• {key}.npy — DACVAE latent representation (pre-computed)

File Structure

data/
  Amusement.tar  (413 samples, 5 buckets)
  Elation.tar  (347 samples, 6 buckets)
  Pleasure_Ecstasy.tar  (202 samples, 5 buckets)
  Contentment.tar  (326 samples, 4 buckets)
  Thankfulness_Gratitude.tar  (419 samples, 5 buckets)
  Affection.tar  (455 samples, 6 buckets)
  Infatuation.tar  (354 samples, 6 buckets)
  Hope_Enthusiasm_Optimism.tar  (498 samples, 7 buckets)
  Triumph.tar  (319 samples, 5 buckets)
  Pride.tar  (410 samples, 5 buckets)
  Interest.tar  (400 samples, 4 buckets)
  Awe.tar  (318 samples, 6 buckets)
  Astonishment_Surprise.tar  (385 samples, 5 buckets)
  Concentration.tar  (381 samples, 5 buckets)
  Contemplation.tar  (401 samples, 5 buckets)
  Relief.tar  (482 samples, 6 buckets)
  Longing.tar  (373 samples, 5 buckets)
  Teasing.tar  (306 samples, 4 buckets)
  Impatience_and_Irritability.tar  (430 samples, 5 buckets)
  Sexual_Lust.tar  (323 samples, 6 buckets)
  Doubt.tar  (310 samples, 5 buckets)
  Fear.tar  (267 samples, 5 buckets)
  Distress.tar  (417 samples, 5 buckets)
  Confusion.tar  (404 samples, 6 buckets)
  Embarrassment.tar  (273 samples, 4 buckets)
  Shame.tar  (370 samples, 6 buckets)
  Disappointment.tar  (415 samples, 5 buckets)
  Sadness.tar  (437 samples, 6 buckets)
  Bitterness.tar  (65 samples, 5 buckets)
  Contempt.tar  (353 samples, 6 buckets)
  Disgust.tar  (211 samples, 4 buckets)
  Anger.tar  (427 samples, 7 buckets)
  Malevolence_Malice.tar  (253 samples, 5 buckets)
  Sourness.tar  (164 samples, 4 buckets)
  Pain.tar  (319 samples, 6 buckets)
  Helplessness.tar  (288 samples, 4 buckets)
  Fatigue_Exhaustion.tar  (410 samples, 5 buckets)
  Emotional_Numbness.tar  (401 samples, 5 buckets)
  Intoxication_Altered_States_of_Consciousness.tar  (349 samples, 6 buckets)
  Jealousy_and_Envy.tar  (309 samples, 5 buckets)
  Valence.tar  (834 samples, 10 buckets)
  Arousal.tar  (489 samples, 7 buckets)
  Submissive_vs._Dominant.tar  (397 samples, 5 buckets)
  Age.tar  (504 samples, 6 buckets)
  Gender.tar  (601 samples, 7 buckets)
  Serious_vs._Humorous.tar  (509 samples, 7 buckets)
  Vulnerable_vs._Emotionally_Detached.tar  (507 samples, 6 buckets)
  Confident_vs._Hesitant.tar  (404 samples, 5 buckets)
  Warm_vs._Cold.tar  (546 samples, 6 buckets)
  Monotone_vs._Expressive.tar  (468 samples, 5 buckets)
  High-Pitched_vs._Low-Pitched.tar  (403 samples, 5 buckets)
  Soft_vs._Harsh.tar  (404 samples, 6 buckets)
  Authenticity.tar  (302 samples, 4 buckets)
  Recording_Quality.tar  (500 samples, 5 buckets)
  Background_Noise.tar  (400 samples, 4 buckets)

Detailed Statistics

Emotion Categories

Category	Dominant Samples	Buckets	Selected	Bucket Distribution
Amusement	47,119	5	413	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):13
Elation	1,585	6	347	[0,1):3, [1,2):100, [2,3):100, [3,4):100, [4,5):37, [5,6):7
Pleasure_Ecstasy	202	5	202	[0,1):4, [1,2):87, [2,3):90, [3,4):20, [4,5):1
Contentment	1,502	4	326	[0,1):85, [1,2):100, [2,3):100, [3,4):41
Thankfulness_Gratitude	43,120	5	419	[0,1):19, [1,2):100, [2,3):100, [3,4):100, [4,5):100
Affection	10,840	6	455	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):54, [5,6):1
Infatuation	4,585	6	354	[0,1):2, [1,2):100, [2,3):100, [3,4):100, [4,5):50, [5,6):2
Hope_Enthusiasm_Optimism	42,840	7	498	[0,1):28, [1,2):100, [2,3):100, [3,4):100, [4,5):100, [5,6):67, [6,7):3
Triumph	2,323	5	319	[0,1):11, [1,2):100, [2,3):100, [3,4):100, [4,5):8
Pride	8,000	5	410	[0,1):93, [1,2):100, [2,3):100, [3,4):100, [4,5):17
Interest	1,760,408	4	400	[0,1):100, [1,2):100, [2,3):100, [3,4):100
Awe	822	6	318	[0,1):3, [1,2):100, [2,3):100, [3,4):100, [4,5):14, [5,6):1
Astonishment_Surprise	19,893	5	385	[0,1):72, [1,2):100, [2,3):100, [3,4):100, [4,5):13
Concentration	358,960	5	381	[0,1):100, [1,2):100, [2,3):100, [3,4):77, [4,5):4
Contemplation	35,067	5	401	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):1
Relief	19,039	6	482	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):80, [5,6):2
Longing	5,631	5	373	[0,1):100, [1,2):100, [2,3):100, [3,4):70, [4,5):3
Teasing	5,011	4	306	[0,1):100, [1,2):100, [2,3):100, [3,4):6
Impatience_and_Irritability	107,965	5	430	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):30
Sexual_Lust	5,306	6	323	[0,1):15, [1,2):100, [2,3):100, [3,4):100, [4,5):7, [5,6):1
Doubt	1,353	5	310	[0,1):100, [1,2):100, [2,3):100, [3,4):7, [4,5):3
Fear	3,023	5	267	[0,1):25, [1,2):100, [2,3):100, [3,4):41, [4,5):1
Distress	23,200	5	417	[0,1):17, [1,2):100, [2,3):100, [3,4):100, [4,5):100
Confusion	17,933	6	404	[0,1):100, [1,2):100, [2,3):100, [3,4):97, [4,5):6, [5,6):1
Embarrassment	2,675	4	273	[0,1):100, [1,2):100, [2,3):72, [3,4):1
Shame	1,881	6	370	[0,1):3, [1,2):100, [2,3):100, [3,4):100, [4,5):63, [5,6):4
Disappointment	6,835	5	415	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):15
Sadness	26,666	6	437	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):36, [5,6):1
Bitterness	65	5	65	[0,1):3, [1,2):41, [2,3):15, [3,4):5, [4,5):1
Contempt	4,201	6	353	[0,1):28, [1,2):100, [2,3):100, [3,4):100, [4,5):24, [6,7):1
Disgust	2,139	4	211	[0,1):8, [1,2):100, [2,3):100, [3,4):3
Anger	4,976	7	427	[0,1):21, [1,2):100, [2,3):100, [3,4):100, [4,5):100, [5,6):5, [8,9):1
Malevolence_Malice	1,736	5	253	[0,1):18, [1,2):100, [2,3):100, [3,4):33, [4,5):2
Sourness	223	4	164	[0,1):34, [1,2):100, [2,3):23, [3,4):7
Pain	2,683	6	319	[0,1):3, [1,2):100, [2,3):100, [3,4):100, [4,5):14, [5,6):2
Helplessness	1,735	4	288	[0,1):36, [1,2):100, [2,3):100, [3,4):52
Fatigue_Exhaustion	17,533	5	410	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):10
Emotional_Numbness	20,435	5	401	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [6,7):1
Intoxication_Altered_States_of_Consciousness	10,247	6	349	[0,1):35, [1,2):100, [2,3):100, [3,4):100, [4,5):13, [5,6):1
Jealousy_&_Envy	3,280	5	309	[0,1):4, [1,2):100, [2,3):100, [3,4):100, [4,5):5

Voice Attributes

Attribute	Buckets	Selected	Bucket Distribution
Valence	10	834	[-5,-4):33, [-4,-3):100, [-3,-2):100, [-2,-1):100, [-1,0):100, [0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):1
Arousal	7	489	[-1,0):3, [0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):83, [5,6):3
Submissive_vs._Dominant	5	397	[-1,0):100, [0,1):100, [1,2):100, [2,3):96, [3,4):1
Age	6	504	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):100, [5,6):4
Gender	7	601	[-5,-4):1, [-3,-2):100, [-2,-1):100, [-1,0):100, [0,1):100, [1,2):100, [2,3):100
Serious_vs._Humorous	7	509	[-1,0):100, [0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):8, [5,6):1
Vulnerable_vs._Emotionally_Detached	6	507	[-1,0):100, [0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):7
Confident_vs._Hesitant	5	404	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):4
Warm_vs._Cold	6	546	[-3,-2):46, [-2,-1):100, [-1,0):100, [0,1):100, [1,2):100, [2,3):100
Monotone_vs._Expressive	5	468	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):68
High-Pitched_vs._Low-Pitched	5	403	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):3
Soft_vs._Harsh	6	404	[-3,-2):2, [-2,-1):100, [-1,0):100, [0,1):100, [1,2):100, [2,3):2
Authenticity	4	302	[1,2):100, [2,3):100, [3,4):100, [4,5):2
Recording_Quality	5	500	[0,1):100, [1,2):100, [2,3):100, [3,4):100, [4,5):100
Background_Noise	4	400	[-1,0):100, [0,1):100, [1,2):100, [2,3):100

Source Dataset

• Source: TTS-AGI/enhanced-audiosnippets-DACVAE
• Emotion Model: Empathic Insight Voice+
• Audio Codec: DACVAE (pre-computed latent representations stored as .npy)

Usage

import webdataset as wds
import json, io, numpy as np

# Load one emotion category
ds = wds.WebDataset("data/Anger.tar")
for sample in ds:
    meta = json.loads(sample["json"])
    dacvae = np.load(io.BytesIO(sample["npy"]))
    print(meta["transcription"], meta["empathic_insight_scores"]["Anger"])

License

Same as source dataset. See TTS-AGI/enhanced-audiosnippets-DACVAE.