MOSS-VoiceGenerator

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.

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

MOSS Voice Generator Model Card

MOSS Voice Generator is an open-source voice generation system designed to enable the creation of custom speaker timbres from free-form textual descriptions. This model allows users to generate voices that reflect specific characters, personalities, and emotions. It is particularly notable for its ability to produce speech with natural-sounding emotional expressiveness, providing a realistic and nuanced listening experience. As an open-source tool, MOSS Voice Generator is suitable for a variety of applications, such as audiobooks, game dubbing, role-playing agents, and conversational assistants.

1. Overview

1.1 TTS Family Positioning

MOSS Voice Generator is a high-fidelity voice design tool within the broader TTS Family. It specializes in crafting expressive and natural-sounding voices from textual descriptions. Unlike traditional TTS systems relying on predefined voices or reference audio, MOSS Voice Generator enables zero-shot voice design, allowing for the creation of customized voices for a variety of applications, such as characters, audiobooks, games, or virtual assistants. Additionally, it can serve as a voice design layer for other TTS systems, addressing the challenge of finding suitable reference audio and improving integration and performance.

Key Capabilities

• Highly expressive emotional delivery: Aimed at generating voices with dynamic and nuanced emotional performances, allowing for natural shifts in tone, pace, and emotion.
• Human-Like Naturalness : Indistinguishable from real human speech with authentic breathing, pauses, and vocal nuances
• Multilingual Support : High-quality synthesis in Chinese and English

1.2 Model Architecture

MOSS Voice Generator employs MossTTSDelay architecture (see moss_tts_delay/README.md for more details), where voice description instructions and the text to be synthesized are concatenated and jointly tokenized as inpu