E1 TTS: Simple and Fast Non-Autoregressive TTS

This paper introduces Easy One-Step Text-to-Speech (E1 TTS), an efficient non-autoregressive zero-shot text-to-speech system based on denoising diffusion pretraining and distribution matching distillation. The training of E1 TTS is straightforward; it does not require explicit monotonic alignment between the text and audio pairs. The inference of E1 TTS is efficient, requiring only one neural network evaluation for each utterance. Despite its sampling efficiency, E1 TTS achieves naturalness and speaker similarity comparable to various strong baseline models. Audio samples are available at e1tts.github.io.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10890230
Citations
3
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
2.02

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article

E1 TTS: Simple and Fast Non-Autoregressive TTS

Pengcheng Zhu, Haizhou Li, Mengxiao Bi, Shuai Wang et al.
3 citations
Advanced Chemical Sensor Technologies
2.02
article

E1 TTS: Simple and Fast Non-Autoregressive TTS

Pengcheng Zhu, Haizhou Li, Mengxiao Bi, Shuai Wang, Zhijun Liu
article en
3 citations

Abstract

This paper introduces Easy One-Step Text-to-Speech (E1 TTS), an efficient non-autoregressive zero-shot text-to-speech system based on denoising diffusion pretraining and distribution matching distillation. The training of E1 TTS is straightforward; it does not require explicit monotonic alignment between the text and audio pairs. The inference of E1 TTS is efficient, requiring only one neural network evaluation for each utterance. Despite its sampling efficiency, E1 TTS achieves naturalness and speaker similarity comparable to various strong baseline models. Audio samples are available at e1tts.github.io.

NetEase (China) (CN), Chinese University of Hong Kong, Shenzhen (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 15%
Advanced Chemical Sensor Technologies
2.02
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E1 TTS: Simple and Fast Non-Autoregressive TTS — Pengcheng Zhu, Haizhou Li, et al. · (2025) | TGRS Research Map | TGRS