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TTS-AGI/balanced-emotion-dataset-majestrino-withtemporal-detailed-captions

Balanced Emotion Dataset — Majestrino with Temporal Detailed Captions An emotion-balanced subset of TTS-AGI/majestrino-unified-detailed-captions-temporal. Overview Total samples: 482,594 Samples per emotion category: 12,997 Number of emotion categories: 40 Format: WebDataset (tar files with FLAC audio + JSON metadata) Number of tar files: 483 Samples per tar: ~1000 Balancing Strategy Samples were selected from the source dataset using keyword… See the full description on the dataset page: https://huggingface.co/datasets/TTS-AGI/balanced-emotion-dataset-majestrino-withtemporal-detailed-captions.

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Dataset Card

Balanced Emotion Dataset — Majestrino with Temporal Detailed Captions

An emotion-balanced subset of TTS-AGI/majestrino-unified-detailed-captions-temporal.

Overview

—Total samples: 482,594
—Samples per emotion category: 12,997
—Number of emotion categories: 40
—Format: WebDataset (tar files with FLAC audio + JSON metadata)
—Number of tar files: 483
—Samples per tar: ~1000

Balancing Strategy

Samples were selected from the source dataset using keyword matching on captions. Each of the 40 emotion categories has exactly 12,997 samples, balanced by the rarest category (Intoxication/Altered States). Samples are spread across diverse source shards for maximum variety. Some samples (~7.3%) appear in multiple categories due to multi-emotion captions.

Emotion Categories

Category	Samples	Example Keywords
Amusement	12997	lighthearted fun, amusement, mirth, joviality, laughter
Elation	12997	happiness, excitement, joy, exhilaration, delight
Pleasure/Ecstasy	12997	ecstasy, pleasure, bliss, rapture, beatitude
Contentment	12997	contentment, relaxation, peacefulness, calmness, satisfaction
Thankfulness/Gratitude	12997	thankfulness, gratitude, appreciation, gratefulness
Affection	12997	sympathy, compassion, warmth, trust, caring
Infatuation	12997	infatuation, having a crush, romantic desire, fondness, butterflies in the stomach
Hope/Optimism	12997	hope, enthusiasm, optimism, anticipation, courage
Triumph	12997	triumph, superiority
Pride	12997	pride, dignity, self-confidently, honor, self-consciousness
Interest	12997	interest, fascination, curiosity, intrigue
Awe	12997	awe, awestruck, wonder
Astonishment/Surprise	12997	astonishment, surprise, amazement, shock, startlement
Concentration	12997	concentration, deep focus, engrossment, absorption, attention
Contemplation	12997	contemplation, thoughtfulness, pondering, reflection, meditation
Relief	12997	relief, respite, alleviation, solace, comfort
Longing	12997	yearning, longing, pining, wistfulness, nostalgia
Teasing	12997	teasing, bantering, mocking playfully, ribbing, provoking lightly
Impatience and Irritability	12997	impatience, irritability, irritation, restlessness, short-temperedness
Sexual Lust	12997	sexual lust, carnal desire, lust, feeling horny, feeling turned on
Doubt	12997	doubt, distrust, suspicion, skepticism, uncertainty
Fear	12997	fear, terror, dread, apprehension, alarm
Distress	12997	worry, anxiety, unease, anguish, trepidation
Confusion	12997	confusion, bewilderment, flabbergasted, disorientation, perplexity
Embarrassment	12997	embarrassment, shyness, mortification, discomfiture, awkwardness
Shame	12997	shame, guilt, remorse, humiliation, contrition
Disappointment	12997	disappointment, regret, dismay, letdown, chagrin
Sadness	12997	sadness, sorrow, grief, melancholy, dejection
Bitterness	12997	resentment, acrimony, bitterness, cynicism, rancor
Contempt	12997	contempt, disapproval, scorn, disdain, loathing
Disgust	12997	disgust, revulsion, repulsion, abhorrence, loathing
Anger	12997	anger, rage, fury, hate, irascibility
Malevolence/Malice	12997	spite, sadism, malevolence, malice, desire to harm
Sourness	12997	sourness, tartness, acidity, acerbity, sharpness
Pain	12997	physical pain, suffering, torment, ache, agony
Helplessness	12997	helplessness, powerlessness, desperation, submission
Fatigue/Exhaustion	12997	fatigue, exhaustion, weariness, lethargy, burnout
Emotional Numbness	12997	numbness, detachment, insensitivity, emotional blunting, apathy
Intoxication/Altered States	12997	being drunk, stupor, intoxication, disorientation, altered perception
Jealousy & Envy	12997	jealousy, envy, covetousness

Data Format

Each tar file contains paired .flac and .json files:

—FLAC: Audio recording
—JSON: Metadata including caption (unified detailed caption with temporal aspects), transcription, duration, characters_per_second, quality scores, and emotion scores

Usage

python

import webdataset as wds

dataset = wds.WebDataset("data/{00000..00482}.tar")
for sample in dataset:
    audio = sample["flac"]  # FLAC bytes
    meta = json.loads(sample["json"])
    caption = meta["caption"]

Source

Built from TTS-AGI/majestrino-unified-detailed-captions-temporal using emotion keyword matching across all 821 training shards.