VoXtream: Full-Stream Text-To-Speech With Extremely Low Latency
We present VoXtream, a fully autoregressive, zero-shot streaming text-to-speech (TTS) system for real-time use that begins speaking from the first word. VoXtream directly maps incoming phonemes to audio tokens using a monotonic alignment scheme and a limited look-ahead that does not delay onset. Built around an incremental phoneme transformer, a temporal transformer predicting semantic and duration tokens, and a depth transformer producing acoustic tokens, VoXtream achieves, to our knowledge, the lowest initial delay among publicly available streaming TTS: 102 ms on GPU. Despite being trained on a mid-scale 9k-hour corpus, it matches or surpasses larger baselines on several metrics, while delivering competitive quality in both output- and full-streaming settings. Demo and code are available at https://herimor.github.io/voxtream.
Authors
- Nikita Torgashov
- Gabriel Skantze (ORCID: https://orcid.org/0000-0002-8579-1790)
- Gustav Eje Henter (ORCID: https://orcid.org/0000-0002-1643-1054)
Institutions
- KTH Royal Institute of Technology (SE)
Publication Details
- Published
- 2026-04-21
- DOI
- https://doi.org/10.1109/icassp55912.2026.11464944
- Primary Topic
- Speech Recognition and Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Technology Development