MOSS-TTSD

Overview

MOSS‑TTS Family is an open‑source speech and sound generation model family from MOSI.AI and the OpenMOSS team. 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.

The model architecture and tokenizer are detailed in the paper MOSS-Audio-Tokenizer: Scaling Audio Tokenizers for Future Audio Foundation Models.

Introduction

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 TTS foundation model, centered on high-fidelity zero-shot voice cloning with controllable long-form synthesis, pronunciation, and multilingual/code-switched speech. It serves as the core engine for scalable narration, dubbing, and voice-driven products.
• MOSS‑TTSD: MOSS-TTSD is a production long-form dialogue model for expressive multi-speaker conversational audio at scale. It supports long-duration continuity, turn-taking control, and zero-shot voice cloning from short references for podcasts, audiobooks, commentary, dubbing, and entertainment dialogue.
• MOSS‑VoiceGenerator: MOSS-VoiceGenerator is an open-source voice design model that creates speaker timbres directly from free-form text, without reference audio. It unifies timbre design, style control, and content synthesis, and can be used standalone or as a voice-design layer for downstream TTS.
• MOSS‑SoundEffect: MOSS-SoundEffect is a high-fidelity text-to-sound model with broad category coverage and controllable duration for real content production. It generates stable audio from prompts across ambience, urban scenes, creatures, human actions, and music-like clips for film, games, interactive media, and data synthesis.
• MOSS‑TTS‑Realtime: MOSS-TTS-Realtime is a context-aware, multi-turn streaming TTS model for real-time voice agents. By conditioning on dialogue history across both text and prior user acoustics, it delivers low-latency synthesis with coherent, consistent voice responses across turns.

Released Models

Supported Languages

MOSS-TTS, MOSS-TTSD and MOSS-TTS-Realtime currently supports 20 languages:

MOSS-TTSD

MOSS-TTSD is a long-form spoken dialogue generation model that enables highly expressive multi-party conversational speech synthesis across multiple languages. It supports continuous long-duration generation, flexible multi-speaker dialogue control, and state-of-the-art zero-shot voice cloning with only short reference audio. MOSS-TTSD is designed for real-world long-form content creation, including podcasts, audiobook, sports and esports commentary, dubbing, crosstalk, and entertainment scenarios.

1. Overview

1.1 TTS Family Positioning

MOSS-TTSD is the Long-Form Dialogue Specialist in our open-source TTS Family. While our foundational models focus on high-fidelity single-speaker synthesis, MOSS-TTSD extends this capability into the realm of complex, multi-party interactions. It is designed to bridge the gap between distinct audio samples and cohesive, continuous conversation.

Design Goals

• Authentic Interaction: Capturing the natural rhythm, overlaps, and dynamics of human conversation.
• Sustained Coherence: Maintaining speaker identity and contextual consistency over extended durations (up to 1 hour).
• Production Adaptability: Serving diverse high-end scenar