--- 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= 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](https://github.com/modelscope/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 ```python 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](https://huggingface.co/datasets/laion/ai-voices-deduplicated) - [ClearerVoice-Studio](https://github.com/modelscope/ClearerVoice-Studio) - [Empathic Insight Voice Plus](https://huggingface.co/laion/Empathic-Insight-Voice-Plus) - [Orange Speaker-wavLM-tbr](https://huggingface.co/Orange/Speaker-wavLM-tbr) ## License CC-BY-4.0