herimor/voxtream-train-9k

Model Card for VoXtream training dataset

This repository contains a training dataset for VoXtream TTS model.

The dataset contains 9k hours:

• 4.5k hours sampled from Emilia dataset. We applied additional diarization to remove multi-speaker utterances and discarded utterances with invalid automatic transcripts. We also used NISQA model to remove low-quality utterances.
• 4.5k hours sampled from HiFiTTS2 dataset (22 kHz subset). We selected only single-speaker utterances and filtered the dataset by the WER.

All utterances are 25-seconds long. For shorter audio clips we concatenated multiple utterances within the same speaker. Sampling rate: 24kHz.

Description

• mimi_codes_16cb - Tokens extracted by the Mimi audio codec (16 codebooks).
• phone_emb_indices - Alignment of phoneme tokens to Mimi audio frames extracted by MFA.
• phone_tokens - Phoneme tokens.
• sem_label_shifts - Monotonic phoneme alignment labels.
• spk_templates - Speaker templates for the first 3 seconds of audio extracted by ReDimNet model.

Sources

• Repository: repo
• Paper: paper
• Demo: demo

Get started

To download the dataset, use the following code:

from huggingface_hub import snapshot_download

local_dir = snapshot_download('herimor/voxtream-train-9k', repo_type='dataset')

Clone our repo and follow the instructions in the README file.

Sample Usage

The following examples demonstrate how to use the VoXtream model (trained on this dataset) for output streaming and full streaming.

Installation

pip install voxtream

Output streaming

voxtream \
    --prompt-audio assets/audio/male.wav \
    --prompt-text "The liquor was first created as 'Brandy Milk', produced with milk, brandy and vanilla." \
    --text "In general, however, some method is then needed to evaluate each approximation." \
    --output "output_stream.wav"

• Note: Initial run may take some time to download model weights.

Full streaming

voxtream \
    --prompt-audio assets/audio/female.wav \
    --prompt-text "Betty Cooper helps Archie with cleaning a store room, when Reggie attacks her." \
    --text "Staff do not always do enough to prevent violence." \
    --output "full_stream.wav" \
    --full-stream

Citation

@article{torgashov2025voxtream,
  author    = {Torgashov, Nikita and Henter, Gustav Eje and Skantze, Gabriel},
  title     = {Vo{X}tream: Full-Stream Text-to-Speech with Extremely Low Latency},
  journal   = {arXiv:2509.15969},
  year      = {2025}
}