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E1 TTS: Simple and Fast Non-Autoregressive TTS

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arxiv 2409.09351 v1 pith:JQII3L7M submitted 2024-09-14 eess.AS cs.SD

Zhijun Liu , Shuai Wang , Pengcheng Zhu , Mengxiao Bi , Haizhou Li This is my paper
classification eess.AScs.SD
keywords audioefficientnon-autoregressivetext-to-speechachievesalignmentavailablebaseline
verification ladder T0 review T1 audit T2 compute T3 formal
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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 http://e1tts.github.io/ .

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching

    eess.AS 2024-10 unverdicted novelty 5.0 of 10

    F5-TTS generates natural speech from text via flow matching on DiT with simple text padding, ConvNeXt refinement, and sway sampling, trained on 100K hours multilingual data.

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