laion/reference-voices-enhanced

Reference Voices Enhanced

2,004 AI voice samples enhanced with ClearerVoice-Studio MossFormer2_SE_48K speech enhancement, annotated with Empathic Insight Voice Plus (59 quality + emotion scores).

Dataset Summary

• Source: laion/ai-voices-deduplicated (2,004 speaker-deduplicated, quality-filtered AI voice samples)
• Speech Enhancement: ClearerVoice MossFormer2_SE_48K — background noise removal and speech clarity improvement
• Output Format: Enhanced WAV files at 48kHz (replacing original MP3s)
• Annotations: Full Empathic Insight Voice Plus scores (59 dimensions: 55 emotion scores + 4 quality scores)
• Metadata: Updated JSON sidecar per sample with all annotation scores
• Packaging: Single tar file

Enhancement Pipeline

1. Source data: 2,004 samples from laion/ai-voices-deduplicated, organized by gender (male/female/androgynous) and age category (child/teenager/young_adult/adult/elderly)
2. Speech enhancement: Each audio sample processed through ClearerVoice-Studio MossFormer2_SE_48K model for noise suppression and speech clarity improvement at 48kHz
3. Format conversion: Original MP3 files replaced with enhanced WAV files at 48kHz sample rate
4. Emotion annotation: All enhanced samples annotated with Empathic Insight Voice Plus, providing 59 scores per sample
5. Metadata update: JSON sidecar files updated with all annotation scores

Structure

reference-voices-enhanced.tar
├── male/
│   ├── 02_child/       (1 sample)
│   ├── 03_teenager/    (5 samples)
│   ├── 04_young_adult/ (217 samples)
│   ├── 05_adult/       (813 samples)
│   └── 08_elderly/     (1 sample)
├── female/
│   ├── 02_child/       (16 samples)
│   ├── 03_teenager/    (3 samples)
│   ├── 04_young_adult/ (376 samples)
│   ├── 05_adult/       (514 samples)
│   └── 08_elderly/     (1 sample)
└── androgynous/
    ├── 02_child/       (13 samples)
    ├── 04_young_adult/ (19 samples)
    └── 05_adult/       (25 samples)

Each sample consists of:

• .wav — Enhanced audio file (48kHz, WAV format)
• .json — Metadata sidecar with caption, emotion scores, and quality scores

Gender Distribution

Gender	Count
Male	1,037
Female	910
Androgynous	57
Total	2,004

Annotations

Quality Scores (4 dimensions)

All samples were quality-filtered in the source dataset with:

• score_background_quality >= 3.5 (DNS MOS background quality)
• score_content_enjoyment >= 5.0 (content enjoyment rating)

The full set of quality scores in each JSON sidecar:

Score	Description
score_background_quality	DNS MOS background quality rating
score_content_enjoyment	Content enjoyment rating
score_overall_quality	Overall audio quality rating
score_speech_quality	Speech-specific quality rating

Emotion Scores (55 dimensions)

Each JSON sidecar contains 55 emotion and vocal characteristic scores from Empathic Insight Voice Plus, including:

• Core emotions: Anger, Disgust, Fear, Sadness, Joy/Happiness, Contentment, Amusement, Affection, Awe
• Complex emotions: Contempt, Confusion, Distress, Disappointment, Bitterness, Nostalgia, Guilt/Shame, Envy/Jealousy
• Social/cognitive: Concentration, Contemplation, Determination, Pride, Relief, Sarcasm/Irony, Triumph
• Surprise variants: Astonishment/Surprise, Excitement
• Vocal characteristics: Age, Arousal, Valence, Dominance, Authenticity, Monotone vs. Expressive, Confident vs. Hesitant, Formal vs. Casual, Fast vs. Slow, Loud vs. Soft, Staccato vs. Legato, Tense vs. Relaxed, Nasal, Breathy/Whisper, Creaky/Vocal Fry, Trembling/Shaky, Lisp/Speech Impediment, Accent Strength
• Additional: Background Noise, Music/Singing, Laughter, Non-speech Sounds, Reverberation, Multiple Speakers

Speech Enhancement Details

The ClearerVoice-Studio MossFormer2_SE_48K model is a state-of-the-art speech enhancement model that:

• Removes background noise while preserving speech quality
• Operates at 48kHz for high-fidelity output
• Uses the MossFormer2 architecture optimized for speech enhancement (SE)
• Produces clean, broadcast-quality speech suitable for TTS reference voices

Source Dataset Lineage

laion/reference_ai_voices_with_timbre_annotations  (17 tar files, ~32,000 samples)
    │
    ├── Quality filtering (score_background_quality >= 3.5, score_content_enjoyment >= 5.0)
    │   → 11,473 samples
    │
    ├── Speaker deduplication (Orange/Speaker-wavLM-tbr embeddings, agglomerative clustering)
    │   → 2,004 unique speakers
    │
    └── laion/ai-voices-deduplicated  (2,004 samples, MP3)
        │
        ├── ClearerVoice MossFormer2_SE_48K speech enhancement
        ├── Format conversion to 48kHz WAV
        ├── Empathic Insight Voice Plus annotation (59 scores)
        │
        └── laion/reference-voices-enhanced  (2,004 samples, WAV @ 48kHz)  ← this dataset

Usage

from huggingface_hub import hf_hub_download
import tarfile

# Download the tar file
path = hf_hub_download(
    "laion/reference-voices-enhanced",
    "reference-voices-enhanced.tar",
    repo_type="dataset"
)

# Extract
with tarfile.open(path) as tar:
    tar.extractall("./reference-voices-enhanced")

Citation

If you use this dataset, please cite the source dataset and the tools used:

• LAION AI Voices Deduplicated
• ClearerVoice-Studio
• Empathic Insight Voice Plus
• Orange Speaker-wavLM-tbr

License

CC-BY-4.0