| --- |
| 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') |
| ``` |
| |
