OpenMOSS-Team
/

MOSS-SoundEffect-v2.0

@@ -14,69 +14,32 @@ tags:
 - sound-effects
 - audio-generation
 ---
-# MOSS-TTS Family
-<br>
 <p align="center">
-  &nbsp;&nbsp;&nbsp;&nbsp;
   <img src="https://speech-demo.oss-cn-shanghai.aliyuncs.com/moss_tts_demo/tts_readme_imgaes_demo/openmoss_x_mosi" height="50" align="middle" />
 </p>
 <div align="center">
-  <a href="https://github.com/OpenMOSS/MOSS-TTS/tree/main"><img src="https://img.shields.io/badge/Project%20Page-GitHub-blue"></a>
-  <a href="https://modelscope.cn/collections/OpenMOSS-Team/MOSS-TTS"><img src="https://img.shields.io/badge/ModelScope-Models-lightgrey?logo=modelscope&amp"></a>
-  <a href="https://mosi.cn/#models"><img src="https://img.shields.io/badge/Blog-View-blue?logo=internet-explorer&amp"></a>
-  <a href="https://arxiv.org/abs/2603.18090"><img src="https://img.shields.io/badge/Arxiv-2603.18090-red?logo=Arxiv&amp"></a>
-  <a href="https://studio.mosi.cn"><img src="https://img.shields.io/badge/AIStudio-Try-green?logo=internet-explorer&amp"></a>
-  <a href="https://studio.mosi.cn/docs/moss-tts"><img src="https://img.shields.io/badge/API-Docs-00A3FF?logo=fastapi&amp"></a>
-  <a href="https://x.com/Open_MOSS"><img src="https://img.shields.io/badge/Twitter-Follow-black?logo=x&amp"></a>
-  <a href="https://discord.gg/fvm5TaWjU3"><img src="https://img.shields.io/badge/Discord-Join-5865F2?logo=discord&amp"></a>
 </div>
-## 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="https://speech-demo.oss-cn-shanghai.aliyuncs.com/moss_tts_demo/tts_readme_imgaes_demo/moss_tts_family_arch.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**: The flagship production model featuring high fidelity and optimal zero-shot voice cloning. It supports **long-speech generation**, **fine-grained control over Pinyin, phonemes, and duration**, as well as **multilingual/code-switched synthesis**.
-- **MOSS‑TTSD**: A spoken dialogue generation model for expressive, multi-speaker, and ultra-long dialogues. The new **v1.0 version** achieves **industry-leading performance on objective metrics** and **outperformed top closed-source models like Doubao and Gemini 2.5-pro** in subjective evaluations. You can visit the [MOSS-TTSD repository](https://github.com/OpenMOSS/MOSS-TTSD) for details.
-- **MOSS‑VoiceGenerator**: An open-source voice design model capable of generating diverse voices and styles directly from text prompts, **without any reference speech**. It unifies voice design, style control, and synthesis, functioning independently or as a design layer for downstream TTS. Its performance **surpasses other top-tier voice design models in arena ratings**.
-- **MOSS‑TTS‑Realtime**: A multi-turn context-aware model for real-time voice agents. It uses incremental synthesis to ensure natural and coherent replies, making it **ideal for building low-latency voice agents when paired with text models**. The TTFB (Time To First Byte) of MOSS-TTS-Realtime reaches 180 ms, and the $T_{\text{LLM-first-sentence}} + T_{\text{MOSS-TTS-Realtime-TTFB}}$ is 377 ms.
-- **MOSS‑SoundEffect**: A content creation model specialized in **sound effect generation** with wide category coverage and controllable duration. It generates audio for natural environments, urban scenes, biological sounds, human actions, and musical fragments, suitable for film, games, and interactive experiences.
----
-## MOSS-SoundEffect-V2.0
 **MOSS-SoundEffect v2.0** is a text-to-audio model with a Diffusion Transformer (DiT) backbone trained with the Flow Matching objective, paired with a DAC VAE and a Qwen3 text encoder. It generates high-fidelity environmental, urban, creature, and human-action sound effects from natural-language prompts, with controllable duration up to 30 seconds at 48 kHz.
-### 1. Overview
-#### 1.1 TTS Family Positioning
 Within the MOSS-TTS Family, MOSS-SoundEffect is the dedicated **text-to-sound** model — the family member that turns natural-language captions into non-speech audio (ambience, urban scenes, creatures, human actions, short music-like clips). v2.0 supersedes the v1 discrete-token autoregressive backbone (`MossTTSDelay`) with a continuous-latent **Diffusion Transformer + Flow Matching** design.
-#### 1.2 Key Capabilities
 - **Broad SFX coverage**: natural environments, urban environments, animals & creatures, human actions, and short musical/percussive clips.
 - **Long-form generation**: stable audio up to **30 seconds** per call with the duration tag prepended to the prompt at training time.
 - **Bilingual prompts**: trained with both **English and Chinese** captions.
-#### 1.3 Released Models
 | Model | Architecture | DiT Variant | Parameters |
 |---|---|---|---:|
@@ -91,9 +54,9 @@ Within the MOSS-TTS Family, MOSS-SoundEffect is the dedicated **text-to-sound**
 | `sigma_shift` | 5.0 | Flow-match scheduler shift applied per call. |
 | `seconds` | 10.0 | Output duration. Up to 30. |
-### 2. Quick Start
-#### Environment Setup
 We recommend a clean, isolated Python 3.12 environment to avoid dependency conflicts with the top-level MOSS-TTS environment.
@@ -114,7 +77,7 @@ pip install --extra-index-url https://download.pytorch.org/whl/cu128 \
     -e ".[torch-cu128]"
 ```
-#### Basic Usage
 ```python
 import torch

 - sound-effects
 - audio-generation
 ---
+# MOSS-SoundEffect-V2.0
 <p align="center">
   <img src="https://speech-demo.oss-cn-shanghai.aliyuncs.com/moss_tts_demo/tts_readme_imgaes_demo/openmoss_x_mosi" height="50" align="middle" />
 </p>
 <div align="center">
+  <a href="https://github.com/OpenMOSS/MOSS-TTS/tree/main/moss_soundeffect_v2"><img src="https://img.shields.io/badge/Project%20Page-GitHub-blue"></a>
 </div>
 **MOSS-SoundEffect v2.0** is a text-to-audio model with a Diffusion Transformer (DiT) backbone trained with the Flow Matching objective, paired with a DAC VAE and a Qwen3 text encoder. It generates high-fidelity environmental, urban, creature, and human-action sound effects from natural-language prompts, with controllable duration up to 30 seconds at 48 kHz.
+## 1. Overview
+### 1.1 TTS Family Positioning
 Within the MOSS-TTS Family, MOSS-SoundEffect is the dedicated **text-to-sound** model — the family member that turns natural-language captions into non-speech audio (ambience, urban scenes, creatures, human actions, short music-like clips). v2.0 supersedes the v1 discrete-token autoregressive backbone (`MossTTSDelay`) with a continuous-latent **Diffusion Transformer + Flow Matching** design.
+### 1.2 Key Capabilities
 - **Broad SFX coverage**: natural environments, urban environments, animals & creatures, human actions, and short musical/percussive clips.
 - **Long-form generation**: stable audio up to **30 seconds** per call with the duration tag prepended to the prompt at training time.
 - **Bilingual prompts**: trained with both **English and Chinese** captions.
+### 1.3 Released Models
 | Model | Architecture | DiT Variant | Parameters |
 |---|---|---|---:|
 | `sigma_shift` | 5.0 | Flow-match scheduler shift applied per call. |
 | `seconds` | 10.0 | Output duration. Up to 30. |
+## 2. Quick Start
+### Environment Setup
 We recommend a clean, isolated Python 3.12 environment to avoid dependency conflicts with the top-level MOSS-TTS environment.
     -e ".[torch-cu128]"
 ```
+### Basic Usage
 ```python
 import torch