Datasets:
metadata
license: cc-by-4.0
task_categories:
- audio-classification
- text-to-speech
tags:
- voice
- speaker-embedding
- deduplicated
- emotion
- quality-filtered
- speech-enhancement
- clearervoice
pretty_name: Reference Voices Enhanced
size_categories:
- 1K<n<10K
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
- 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) - Speech enhancement: Each audio sample processed through ClearerVoice-Studio
MossFormer2_SE_48Kmodel for noise suppression and speech clarity improvement at 48kHz - Format conversion: Original MP3 files replaced with enhanced WAV files at 48kHz sample rate
- Emotion annotation: All enhanced samples annotated with Empathic Insight Voice Plus, providing 59 scores per sample
- 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