mlsanityData to 7 Oct 2026

Seed-TTS: A Family of High-Quality Versatile Speech Generation Models

arXiv 2406.02430 ↗First posted 4 Jun 2024eess.AS cs.SDcited by 293

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Cited by 73 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We introduce Seed-TTS, a family of large-scale autoregressive text-to-speech (TTS) models capable of generating speech that is virtually indistinguishable from human speech. Seed-TTS serves as a foundation model for speech generation and excels in speech in-context learning, achieving performance in speaker similarity and naturalness that matches ground truth human speech in both objective and subjective evaluations. With fine-tuning, we achieve even higher subjective scores across these metrics. Seed-TTS offers superior controllability over various speech attributes such as emotion and is capable of generating highly expressive and diverse speech for speakers in the wild. Furthermore, we propose a self-distillation method for speech factorization, as well as a reinforcement learning approach to enhance model robustness, speaker similarity, and controllability. We additionally present a non-autoregressive (NAR) variant of the Seed-TTS model, named Seed-TTSDiT, which utilizes a fully diffusion-based architecture. Unlike previous NAR-based TTS systems, Seed-TTSDiT does not depend on pre-estimated phoneme durations and performs speech generation through end-to-end processing. We demonstrate that this variant achieves comparable performance to the language model-based variant and showcase its effectiveness in speech editing. We encourage readers to listen to demos at urlhttps://bytedancespeech.github.io/seedttstechreport.

Key facts. Cited by 293 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jun 2024.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 24; 2025: 131; 2026: 138.

293 papers.

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  1. 2025Qwen2.5-Omni Technical Reportcited by 704
  2. 2025Qwen3-Omni Technical Reportcited by 451
  3. 2024F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matchingcited by 353
  4. 2024CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Modelscited by 282
  5. 2024MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformercited by 159
  6. 2026Qwen3.5-Omni Technical Reportcited by 146
  7. 2025CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-trainingcited by 142
  8. 2024WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modelingcited by 124
  9. 2025Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokenscited by 109
  10. 2026Qwen3-TTS Technical Reportcited by 106
  11. 2025Step-Audio 2 Technical Reportcited by 101
  12. 2024WavChat: A Survey of Spoken Dialogue Modelscited by 88
38 more
  1. 2024Recent Advances in Speech Language Models: A Surveycited by 85
  2. 2025IndexTTS2: A Breakthrough in Emotionally Expressive and Duration-Controlled Auto-Regressive Zero-Shot Text-to-Speechcited by 85
  3. 2025Step-Audio: Unified Understanding and Generation in Intelligent Speech Interactioncited by 83
  4. 2025Ovi: Twin Backbone Cross-Modal Fusion for Audio-Video Generationcited by 76
  5. 2025Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesiscited by 69
  6. 2024Autoregressive Speech Synthesis without Vector Quantizationcited by 65
  7. 2026MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interactioncited by 64
  8. 2024Language Model Can Listen While Speakingcited by 62
  9. 2025Ming-Omni: A Unified Multimodal Model for Perception and Generationcited by 62
  10. 2025MiMo-Audio: Audio Language Models are Few-Shot Learnerscited by 58
  11. 2025DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generationcited by 56
  12. 2025Recent Advances in Discrete Speech Tokens: A Reviewcited by 42
  13. 2025MegaTTS 3: Sparse Alignment Enhanced Latent Diffusion Transformer for Zero-Shot Speech Synthesiscited by 39
  14. 2025MeViS: A Multi-Modal Dataset for Referring Motion Expression Video Segmentationcited by 34
  15. 2025EmoVoice: LLM-based Emotional Text-To-Speech Model with Freestyle Text Promptingcited by 33
  16. 2024DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factorscited by 31
  17. 2025VITA-Audio: Fast Interleaved Cross-Modal Token Generation for Efficient Large Speech-Language Modelcited by 30
  18. 2025ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow Matchingcited by 30
  19. 2026LongCat-Next: Lexicalizing Modalities as Discrete Tokenscited by 30
  20. 2025VibeVoice Technical Reportcited by 28
  21. 2024Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Surveycited by 27
  22. 2025IndexTTS: An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech Systemcited by 27
  23. 2025InteractiveOmni: A Unified Omni-modal Model for Audio-Visual Multi-turn Dialoguecited by 27
  24. 2025Koel-TTS: Enhancing LLM based Speech Generation with Preference Alignment and Classifier Free Guidancecited by 26
  25. 2025SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modelingcited by 26
  26. 2025SALMONN-omni: A Standalone Speech LLM without Codec Injection for Full-duplex Conversationcited by 25
  27. 2025F5R-TTS: Improving Flow-Matching based Text-to-Speech with Group Relative Policy Optimizationcited by 24
  28. 2025EmergentTTS-Eval: Evaluating TTS Models on Complex Prosodic, Expressiveness, and Linguistic Challenges Using Model-as-a-Judgecited by 24
  29. 2025Streaming Sequence-to-Sequence Learning with Delayed Streams Modelingcited by 24
  30. 2024Towards Controllable Speech Synthesis in the Era of Large Language Models: A Systematic Surveycited by 22
  31. 2026OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Modelscited by 22
  32. 2024Preference Alignment Improves Language Model-Based TTScited by 21
  33. 2025Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generationcited by 21
  34. 2025Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Datacited by 21
  35. 2025Emilia: A Large-Scale, Extensive, Multilingual, and Diverse Dataset for Speech Generationcited by 19
  36. 2025M2-omni: Advancing Omni-MLLM for Comprehensive Modality Support with Competitive Performancecited by 19
  37. 2025MoonCast: High-Quality Zero-Shot Podcast Generationcited by 18
  38. 2024SimpleSpeech 2: Towards Simple and Efficient Text-to-Speech with Flow-based Scalar Latent Transformer Diffusion Modelscited by 17

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