OpenMOSS-Team
/

MOSS-TTS-Realtime

+---
+license: apache-2.0
+---
+# MOSS-TTS Family
+## Overview
+MOSS‑TTS Family is an open‑source **speech and sound generation model family** from [MOSI.AI](https://mosi.cn/#hero) and the [OpenMOSS team](https://www.open-moss.com/). It is designed for **high‑fidelity**, **high‑expressiveness**, and **complex real‑world scenarios**, covering stable long‑form speech, multi‑speaker dialogue, voice/character design, environmental sound effects, and real‑time streaming TTS.
+## Introduction
+<p align="center">
+  <img src="./assets/moss_tts_family.jpeg" width="85%" />
+</p>
+When a single piece of audio needs to **sound like a real person**, **pronounce every word accurately**, **switch speaking styles across content**, **remain stable over tens of minutes**, and **support dialogue, role‑play, and real‑time interaction**, a single TTS model is often not enough. The **MOSS‑TTS Family** breaks the workflow into five production‑ready models that can be used independently or composed into a complete pipeline.
+- **MOSS‑TTS**: MOSS-TTS is the flagship, production-ready Text-to-Speech foundation model in the MOSS-TTS Family, built to ship, scale, and deliver real-world voice applications beyond demos. It provides high-fidelity zero-shot voice cloning as the core capability, along with ultra-long speech generation, token-level duration control, multilingual and code-switched synthesis, and fine-grained Pinyin/phoneme pronunciation control. Together, these features make it a robust base model for scalable narration, dubbing, and voice-driven products.
+- **MOSS‑TTSD**: MOSS-TTSD is a production-oriented long-form spoken dialogue generation model for creating highly expressive, multi-party conversational audio at scale. It supports continuous long-duration generation, flexible multi-speaker turn-taking control, and zero-shot voice cloning from short reference audio, enabling natural conversations with rich interaction dynamics. It is designed for real-world long-form content such as podcasts, audiobooks, commentary, dubbing, and entertainment dialogue.
+- **MOSS‑VoiceGenerator**: MOSS-VoiceGenerator is an open-source voice design system that generates speaker timbres directly from free-form text descriptions, enabling fast creation of voices for characters, personalities, and emotions—without requiring reference audio. It unifies timbre design, style control, and content synthesis in a single instruction-driven model, producing high-fidelity, emotionally expressive speech that feels naturally human. It can be used standalone for creative production, or as a voice design layer that improves integration and usability for downstream TTS systems.
+- **MOSS‑SoundEffect**: MOSS-SoundEffect is a high-fidelity sound effect generation model built for real-world content creation, offering strong environmental richness, broad category coverage, and reliable duration controllability. Trained on large-scale, high-quality data, it generates consistent audio from text prompts across natural ambience, urban scenes, creatures, human actions, and music-like clips. It is well suited for film and game production, interactive experiences, and data synthesis pipelines.
+- **MOSS‑TTS‑Realtime**: MOSS-TTS-Realtime is a context-aware, multi-turn streaming TTS foundation model designed for real-time voice agents. Unlike conventional TTS that synthesizes replies in isolation, it conditions generation on multi-turn dialogue history—including both textual and acoustic signals from prior user speech—so responses stay coherent, consistent, and natural across turns. With low-latency incremental synthesis and strong voice stability, it enables truly conversational, human-like real-time speech experiences.
+## Released Models
+| Model | Architecture | Size | Model Card | Hugging Face |
+|---|---|---:|---|---|
+| **MOSS-TTS** | MossTTSDelay | 8B | [moss_tts_model_card.md](https://github.com/OpenMOSS/MOSS-TTS/blob/main/moss_tts_model_card.md) | 🤗 [Huggingface](https://huggingface.co/OpenMOSS-Team/MOSS-TTS) |
+|  | MossTTSLocal | 1.7B | [moss_tts_model_card.md](https://github.com/OpenMOSS/MOSS-TTS/blob/main/moss_tts_model_card.md) | 🤗 [Huggingface](https://huggingface.co/OpenMOSS-Team/MOSS-TTS-Local-Transformer) |
+| **MOSS‑TTSD‑V1.0** | MossTTSDelay | 8B | [moss_ttsd_model_card.md](https://github.com/OpenMOSS/MOSS-TTS/blob/main/moss_ttsd_model_card.md) | 🤗 [Huggingface](https://huggingface.co/OpenMOSS-Team/MOSS-TTSD-v1.0) |
+| **MOSS‑VoiceGenerator** | MossTTSDelay | 1.7B | [moss_voice_generator_model_card.md](https://github.com/OpenMOSS/MOSS-TTS/blob/main/moss_voice_generator_model_card.md) | 🤗 [Huggingface](https://huggingface.co/OpenMOSS-Team/MOSS-Voice-Generator) |
+| **MOSS‑SoundEffect** | MossTTSDelay | 8B | [moss_sound_effect_model_card.md](https://github.com/OpenMOSS/MOSS-TTS/blob/main/moss_sound_effect_model_card.md) | 🤗 [Huggingface](https://huggingface.co/OpenMOSS-Team/MOSS-SoundEffect) |
+| **MOSS‑TTS‑Realtime** | MossTTSRealtime | 1.7B | [moss_tts_realtime_model_card.md](https://github.com/OpenMOSS/MOSS-TTS/blob/main/moss_tts_realtime_model_card.md) | 🤗 [Huggingface](https://huggingface.co/OpenMOSS-Team/MOSS-TTS-Realtime) |
+## 1. Overview
+### 1.1 TTS Family Positioning
+**MOSS-TTS-Realtime** is a high-performance, real-time speech synthesis model within the broader MOSS TTS Family. It is designed for interactive voice agents that require low-latency, continuous speech generation across multi-turn conversations. Unlike conventional streaming TTS systems that synthesize each response in isolation, MOSS-TTS-Realtime natively models dialogue context by conditioning speech generation on both textual and acoustic information from previous turns. By tightly integrating multi-turn context awareness with incremental streaming synthesis, it produces natural, coherent, and voice-consistent audio responses, enabling fluid and human-like spoken interactions for real-time applications.
+**Key Capabilities**
+* **Context-Aware & Expressive Speech Generation**: Generates expressive and coherent speech by modeling both textual and acoustic context across multiple dialogue turns.
+* **High-Fidelity Voice Cloning with Multi-Turn Consistency**: Achieves exceptionally high voice similarity while maintaining strong speaker identity consistency across multiple dialogue turns.
+* **Long-Context**: Supports long-range context with a maximum context length of 32K (about 40 minutes), enabling stable and consistent speech generation in extended conversations.
+* **Highly Human-Like Speech with Natural Prosody**: Trained on over 2.5 million hours of single-speaker speech and more than 1 million hours of two-speaker and multi-speaker conversational data, resulting in highly natural prosody and strong human-like expressiveness.
+* **Multilingual Speech Support**: Supports over 10 languages beyond Chinese and English, including Korean, Japanese, German, and French, enabling consistent and expressive speech across languages.
+### 1.2 Model Architecture
+## 2. Usage
+Please refer to the following GitHub repository for detailed usage instructions and examples:
+👉 **Usage Guide & Demos**:
+https://github.com/OpenMOSS/MOSS-TTS/blob/main/moss_tts_realtime_model_card.md
+---