# FireRedTTS-2: Towards Long Conversational Speech Generation for Podcast and Chatbot

arXiv: https://arxiv.org/abs/2509.02020 · HTML: https://mlsanity.com/paper/2509.02020/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Sep 2025.

## Built on by (most cited first, 30 of 35)

- [Qwen3-TTS Technical Report](https://mlsanity.com/paper/2601.15621/) (2026)
- [Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generation](https://mlsanity.com/paper/2510.24821/) (2025)
- [Ming-UniAudio: Speech LLM for Joint Understanding, Generation and Editing with Unified Representation](https://mlsanity.com/paper/2511.05516/) (2025)
- [MOSS-TTS Technical Report](https://mlsanity.com/paper/2603.18090/) (2026)
- [Fish Audio S2 Technical Report](https://mlsanity.com/paper/2603.08823/) (2026)
- [Step-Audio-EditX Technical Report](https://mlsanity.com/paper/2511.03601/) (2025)
- [dots.tts Technical Report](https://mlsanity.com/paper/2606.07080/) (2026)
- [FunCineForge: A Unified Dataset Toolkit and Model for Zero-Shot Movie Dubbing in Diverse Cinematic Scenes](https://mlsanity.com/paper/2601.14777/) (2026)
- [SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis](https://mlsanity.com/paper/2602.07803/) (2026)
- [Sarashina2.2-TTS: Tackling Kanji Polyphony in Japanese Speech Generation via Data Scaling and Targeted Data Synthesis](https://mlsanity.com/paper/2606.25369/) (2026)
- [MOSS-TTSD: Text to Spoken Dialogue Generation](https://mlsanity.com/paper/2603.19739/) (2026)
- [TTS-PRISM: A Perceptual Reasoning and Interpretable Speech Model for Fine-Grained Diagnosis](https://mlsanity.com/paper/2604.22225/) (2026)
- [FireRedAudio: A General-Purpose Audio Language Model with Decoupled Continuous Representations for Understanding and Generation](https://mlsanity.com/paper/2608.24168/) (2026)
- [MimicLM: Zero-Shot Voice Imitation through Autoregressive Modeling of Pseudo-Parallel Speech Corpora](https://mlsanity.com/paper/2604.11552/) (2026)
- [Kinetic-Optimal Scheduling with Moment Correction for Metric-Induced Discrete Flow Matching in Zero-Shot Text-to-Speech](https://mlsanity.com/paper/2605.09386/) (2026)
- [WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling](https://mlsanity.com/paper/2606.03455/) (2026)
- [FlashTTS: Fast Streaming TTS with MTP Acceleration and X-pred Mean Flow Distillation](https://mlsanity.com/paper/2606.09141/) (2026)
- [HPRO: Hierarchical Progressive Reward Optimization via Preference Extraction for Emotional Text-to-Speech](https://mlsanity.com/paper/2606.28249/) (2026)
- [DELTA-TTS: Adapting Autoregressive Model into Diffusion Language Model for Text-to-Speech](https://mlsanity.com/paper/2607.04140/) (2026)
- [AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing](https://mlsanity.com/paper/2609.08936/) (2026)
- [Fed-PISA: Federated Voice Cloning via Personalized Identity-Style Adaptation](https://mlsanity.com/paper/2509.16010/) (2025)
- [What Counts as Real? Speech Restoration and Voice Quality Conversion Pose New Challenges to Deepfake Detection](https://mlsanity.com/paper/2603.14033/) (2026)
- [SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness](https://mlsanity.com/paper/2603.14889/) (2026)
- [Conditioned in Training, Dispensable at Inference: Typological Conditioning for Multilingual Speech Translation](https://mlsanity.com/paper/2605.16026/) (2026)
- [PilotTTS: A Disciplined Modular Recipe for Competitive Speech Synthesis](https://mlsanity.com/paper/2605.27258/) (2026)
- [Efficient ASR Training with Conversations that Never Happened](https://mlsanity.com/paper/2606.03957/) (2026)
- [TLDR: Compressing Audio Tokens for Efficient Autoregressive Text-to-Speech](https://mlsanity.com/paper/2606.09019/) (2026)
- [Mask, Sample, Revise: A Revisable CTMC Inference Stack for Guided Discrete Flow Matching Text-to-Speech](https://mlsanity.com/paper/2606.13989/) (2026)
- [EmoInstruct-TTS: Dual-Path Instruction-Guided Emotional Speech Synthesis](https://mlsanity.com/paper/2606.20650/) (2026)
- [ZipL-Dialog: Memory-Efficient Long-Form Spoken Dialog Synthesis via Latent Flow Matching](https://mlsanity.com/paper/2607.12496/) (2026)

## Abstract (arXiv)

Current dialogue generation approaches typically require the complete dialogue text before synthesis and produce a single, inseparable speech containing all voices, making them unsuitable for interactive chat; moreover, they suffer from unstable synthesis, inaccurate speaker transitions, and incoherent prosody. In this work, we present FireRedTTS-2, a long-form streaming TTS system for multi-speaker dialogue generation, delivering stable, natural speech with reliable speaker switching and context-aware prosody. A new 12.5Hz streaming speech tokenizer accelerates training and inference, extends maximum dialogue length, encodes richer semantics to stabilize text-to-token modeling and supports high-fidelity streaming generation for real-time applications. We adopt a text-speech interleaved format, concatenating speaker-labeled text with aligned speech tokens in chronological order, and model it with a dual-transformer: a large decoder-only transformer predicts tokens at the first layer, and a smaller one completes subsequent layers. Experimental results show that FireRedTTS-2 integrates seamlessly with chat frameworks and, with minimal fine-tuning, produces emotionally expressive speech guided by implicit contextual cues. In podcast generation, it surpasses existing systems including MoonCast, Zipvoice-Dialogue, and MOSS-TTSD in objective intelligibility, speaker-turn reliability, and perceived naturalness with context-consistent prosody. Our demos are available at https://fireredteam.github.io/demos/firered_tts_2.