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language:
- en
license: cc-by-4.0
configs:
- config_name: default
data_files:
- split: emilia
path: emilia/*
- split: hifitts2
path: hifitts2/*
splits:
- name: emilia
num_examples: 2240471
- name: hifitts2
num_examples: 713769
tags:
- text-to-speech
task_categories:
- text-to-speech
---
# Model Card for VoXtream2 training dataset
This repository contains a training dataset for [VoXtream2](https://huggingface.co/voxtream2/model) TTS model.
The dataset contains 40k hours:
- 30k hours subset from [Emilia](https://huggingface.co/datasets/amphion/Emilia-Dataset) dataset.
- 10k hours subset from [HiFiTTS2](https://huggingface.co/datasets/nvidia/hifitts-2) dataset (22 kHz).
All utterances are 55 seconds long. We concatenated multiple utterances within the same speaker and padded shorter clips with silence. Sampling rate: 24kHz.
### Description
- **mimi_codes** - Tokens extracted by the [Mimi](https://huggingface.co/kyutai/mimi) audio codec (16 codebooks).
- **phone_emb_indices** - Alignment of phoneme tokens to Mimi audio frames extracted by [ClapIPA](https://github.com/lingjzhu/clap-ipa) forced aligner.
- **phone_tokens** - IPA Phoneme tokens extracted with [espeak-ng](https://github.com/espeak-ng/espeak-ng) phonemizer.
- **sem_label_shifts** - Monotonic phoneme alignment labels.
- **punctuation** - Punctuation tokens.
- **spk_templates** - Speaker templates for the first 3 seconds of audio extracted by [ReDimNet](https://github.com/IDRnD/redimnet) model.
## Usage
To download the dataset, use the following code:
```bash
from huggingface_hub import snapshot_download
local_dir = snapshot_download('voxtream2/train', repo_type='dataset')
```
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