mlsanityData to 7 Oct 2026

E1 TTS: Simple and Fast Non-Autoregressive TTS

arXiv 2409.09351 ↗First posted 14 Sep 2024eess.AS cs.SDcited by 7

On the map: Diffusion models → Audio, speech and music

Abstract (arXiv)

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/ .

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Placed in Audio, speech and music, one of 14 directions in Diffusion models. Builds on 38 of its 50 references that are in the map. First posted on arXiv 14 Sep 2024.

Builds on

38 of 50 references.

Closest ancestors · 11

Same direction, newest first

  1. 2024Sample-Efficient Diffusion for Text-To-Speech Synthesis1 Sep
  2. 2024Autoregressive Diffusion Transformer for Text-to-Speech Synthesis8 Jun
  3. 2024SimpleSpeech: Towards Simple and Efficient Text-to-Speech with Scalar Latent Transformer Diffusion Models4 Jun
  4. 2024FlashSpeech: Efficient Zero-Shot Speech Synthesis23 Apr
  5. 2023E3 TTS: Easy End-to-End Diffusion-based Text to Speech2 Nov
  6. 2023ReFlow-TTS: A Rectified Flow Model for High-fidelity Text-to-Speech29 Sep
  7. 2023VoiceFlow: Efficient Text-to-Speech with Rectified Flow Matching10 Sep
  8. 2023StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models13 Jun
  9. 2023CoMoSpeech: One-Step Speech and Singing Voice Synthesis via Consistency Model11 May
  10. 2023DiffVoice: Text-to-Speech with Latent Diffusion23 Apr
  11. 2022ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech13 Jul

Other references · 27

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  3. 2022Scalable Diffusion Models with Transformerscited by 5,931
  4. 2021RoFormer: Enhanced Transformer with Rotary Position Embeddingcited by 4,581
  5. 2022Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flowcited by 3,550
  6. 2023Consistency Modelscited by 1,778
  7. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,207
  8. 2024Improved Distribution Matching Distillation for Fast Image Synthesiscited by 648
  9. 2019LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speechcited by 639
  10. 2021Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speechcited by 555
  11. 2023Analyzing and Improving the Training Dynamics of Diffusion Modelscited by 396
  12. 2023Voicebox: Text-Guided Multilingual Universal Speech Generation at Scalecited by 373
15 more
  1. 2024CosyVoice: A Scalable Multilingual Zero-shot Text-to-speech Synthesizer based on Supervised Semantic Tokenscited by 323
  2. 2024Seed-TTS: A Family of High-Quality Versatile Speech Generation Modelscited by 293
  3. 2021YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyonecited by 277
  4. 2022BigVGAN: A Universal Neural Vocoder with Large-Scale Trainingcited by 245
  5. 2023Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Modelscited by 232
  6. 2023LCM-LoRA: A Universal Stable-Diffusion Acceleration Modulecited by 211
  7. 2021A Survey on Neural Speech Synthesiscited by 182
  8. 2020FastPitch: Parallel Text-to-speech with Pitch Predictioncited by 150
  9. 2024E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTScited by 149
  10. 2017Deep Voice: Real-time Neural Text-to-Speechcited by 83
  11. 2024ELLA-V: Stable Neural Codec Language Modeling with Alignment-guided Sequence Reorderingcited by 50
  12. 2021One TTS Alignment To Rule Them Allcited by 47
  13. 2023UniCATS: A Unified Context-Aware Text-to-Speech Framework with Contextual VQ-Diffusion and Vocodingcited by 37
  14. 2024Diffusion Models Are Innate One-Step Generatorscited by 15
  15. 2021VARA-TTS: Non-Autoregressive Text-to-Speech Synthesis based on Very Deep VAE with Residual Attentioncited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 2; 2026: 3.

7 papers.

  1. 2024F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matchingcited by 353
  2. 2025Recent Advances in Discrete Speech Tokens: A Reviewcited by 42
  3. 2024Towards Controllable Speech Synthesis in the Era of Large Language Models: A Systematic Surveycited by 22
  4. 2025Pseudo-Autoregressive Neural Codec Language Models for Efficient Zero-Shot Text-to-Speech Synthesiscited by 10
  5. 2026ARCHI-TTS: A flow-matching-based Text-to-Speech Model with Self-supervised Semantic Aligner and Accelerated Inferencecited by 1
  6. 2026Ramsa: A Large Sociolinguistically Rich Emirati Arabic Speech Corpus for ASR and TTScited by 0
  7. 2026A Novel Automatic Framework for Speaker Drift Detection in Synthesized Speechcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024SimpleSpeech 2: Towards Simple and Efficient Text-to-Speech with Flow-based Scalar Latent Transformer Diffusion Models
  2. 2026CuteTTS: Efficient and High-Quality Speech Synthesis via Autoregressive Modeling of Continuous Latents
  3. 2021Diff-TTS: A Denoising Diffusion Model for Text-to-Speech
  4. 2026dots.tts Technical Report
  5. 2023Mega-TTS: Zero-Shot Text-to-Speech at Scale with Intrinsic Inductive Bias
  6. 2025From Text to Talk: Audio-Language Model Needs Non-Autoregressive Joint Training
  7. 2025DiFlow-TTS: Compact and Low-Latency Zero-Shot Text-to-Speech with Discrete Flow Matching
  8. 2024StyleTTS-ZS: Efficient High-Quality Zero-Shot Text-to-Speech Synthesis with Distilled Time-Varying Style Diffusion