Datasets:

Modalities:
Audio
Text
Formats:
parquet
Languages:
Japanese
License:
irodori-refs-10k / README.md
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---
license: apache-2.0
task_categories:
- text-to-speech
language:
- ja
size_categories:
- 10K<n<100K
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 48000
- name: text
dtype: string
- name: speaker_id
dtype: string
splits:
- name: train
num_examples: 10000
configs:
- config_name: default
data_files:
- split: train
path: data/train-*.parquet
---
# Irodori TTS Reference Voices (10K)
10,000 synthetic Japanese reference voices generated with the
[Irodori-TTS-500M-v2-VoiceDesign](https://huggingface.co/Aratako/Irodori-TTS-500M-v2-VoiceDesign)
model from voice-design captions (no reference audio — `no_ref=True`).
Each row is one unique speaker.
## Columns
| column | type | description |
|---|---|---|
| `audio` | Audio(48kHz mono) | reference waveform |
| `text` | string | Japanese utterance with emoji prosody cues |
| `speaker_id` | string | `speaker_00001``speaker_10000` |
## Related datasets
- **Clones (2.99M)** — [SynDataLab/irodori-clones-3m](https://huggingface.co/datasets/SynDataLab/irodori-clones-3m):
299 additional utterances generated in each reference voice using the main
Irodori-TTS-500M-v2 model with latents encoded from these reference audios.
Join on `speaker_id` to link each clone to its reference.
## Generation
- Model: `Aratako/Irodori-TTS-500M-v2-VoiceDesign`
- Codec: `Aratako/Semantic-DACVAE-Japanese-32dim`
- Precision: bf16, `num_steps=40`, `truncation_factor=0.9`,
`rescale_k=0.96`, `rescale_sigma=3.0`, `cfg_scale_text=3.0`,
`cfg_scale_caption=3.0`