datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
laions_got_talent_enhanced_no_metadatamls-enhanced-dacvae
Multilingual LibriSpeech converted to DAC VAE latents
Source
facebook/multilingual_librispeech
Format
Each tar shard (~2GB) contains samples with three files per sample:
{sample_key}.audio.flac # Original audio (FLAC, original sample rate)
{sample_key}.dacvae.npy # DAC VAE latent [T_latent, 128] numpy float32
{sample_key}.metadata.json # All metadata + duration_seconds + chars_per_second
DAC VAE Latent Format
Model:… See the full description on the dataset page: https://huggingface.co/datasets/TTS-AGI/mls-enhanced-dacvae.enhanced-audiosnippets-DACVAEreference-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… See the full description on the dataset page: https://huggingface.co/datasets/laion/reference-voices-enhanced.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.… See the full description on the dataset page: https://huggingface.co/datasets/TTS-AGI/enhanced-emo-snippets-balanced-DACVAE.openslr_enhancedeurospeech-enhanced-dacvae
EuroSpeech parliamentary speech converted to DAC VAE latents
Source
disco-eth/EuroSpeech
Format
Each tar shard (~2GB) contains samples with three files per sample:
{sample_key}.audio.flac # Original audio (FLAC, original sample rate)
{sample_key}.dacvae.npy # DAC VAE latent [T_latent, 128] numpy float32
{sample_key}.metadata.json # All metadata + duration_seconds + chars_per_second
DAC VAE Latent Format
Model:… See the full description on the dataset page: https://huggingface.co/datasets/laion/eurospeech-enhanced-dacvae.ai-voices-enhanced