This paper introduces HiFiTTS-2, a large-scale speech dataset designed for high-bandwidth speech synthesis. The dataset is derived from LibriVox audiobooks, and contains approximately 36.7k hours of English speech for 22.05 kHz training, and 31.7k hours for 44.1 kHz training. We present our data processing pipeline, including bandwidth estimation, segmentation, text preprocessing, and multi-speaker detection. The dataset is accompanied by detailed utterance and audiobook metadata generated by our pipeline, enabling researchers to apply data quality filters to adapt the dataset to various use cases. Experimental results demonstrate that our data pipeline and resulting dataset can facilitate the training of high-quality, zero-shot text-to-speech (TTS) models at high bandwidths.
@article{arxiv.2506.04152,
title = {HiFiTTS-2: A Large-Scale High Bandwidth Speech Dataset},
author = {Ryan Langman and Xuesong Yang and Paarth Neekhara and Shehzeen Hussain and Edresson Casanova and Evelina Bakhturina and Jason Li},
journal= {arXiv preprint arXiv:2506.04152},
year = {2025}
}