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MOSS-TTS Family

GitHub stars: 4.1K GitHub forks: 374 Declared license: Apache-2.0: Apache-2.0 Last pushed September 6, 2026: Pushed 19d ago
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MOSS-TTS Family is a public speech and sound generation model family from MOSI.AI and the OpenMOSS team, covering long-form text-to-speech, voice design, spoken dialogue, realtime TTS, and sound effects.

The repository frames the family as a set of related speech-generation models rather than one narrow TTS checkpoint, with recent materials including MOSS-TTS-v1.5 and the MOSS-SoundEffect-v2.0 text-to-audio release. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.

What it is

A speech and sound model family

MOSS-TTS Family brings together several related releases for voice generation, including a flagship TTS model, spoken-dialogue generation, prompt-based voice design, realtime speech for voice agents, compact speech generation, and sound-effect generation.

Why it stands out

Broader than a single TTS demo

The range is the point: one family covers multilingual synthesis, voice cloning, long-form generation, dialogue, realtime responses, pronunciation or pause control, compact local speech, and generated sound effects.

Availability

Repository, model cards, and demo links

The source materials include the GitHub repository, Hugging Face model pages, a model collection, quickstart notes, backend paths, demos, and a separate MOSS-SoundEffect v2 subfolder for readers who want to inspect the sound-generation path more closely.

Why it matters

What makes it useful

MOSS-TTS is a family of separate speech and sound-effect releases, so one setup guide cannot stand in for the collection. A reader building narration, realtime replies, or effects can start with the matching model card and its dependencies before testing output.

Notable points

What stands out

MOSS-TTS-v1.5, the realtime and Nano routes, and MOSS-SoundEffect-v2.0 have separate model cards or folders. The SoundEffect v2.0 model card lists 1.3B parameters; its README describes a DiT and Flow Matching pipeline with a DAC VAE and Qwen3 text encoder. It needs its own environment, so choose the speech or sound job before following a setup path.

Before using

What to review

Which family member fits the intended job: general TTS, dialogue, voice design, realtime speech, compact local use, or sound effects.

The current model-card notes, setup requirements, backend choices, and hardware assumptions before planning a workflow.

For MOSS-SoundEffect v2.0, the separate Python environment and dependency notes in the subfolder README.

Consent, identity, voice-cloning, and platform rules when working with reference voices or generated speech that may sound like a person.

Reader fit

Who may find it relevant

Readers following speech-generation models beyond basic text-to-speech.

Builders comparing voice-output options for agents, narration, dialogue, multilingual speech, compact local speech, or sound design.

Creative-tool builders comparing text-to-audio paths for environmental sounds, interface sounds, games, video, or interactive experiences.

Less relevant for readers looking for a simple hosted voice API or a general-purpose chatbot interface.

Editorial note

Why LifeHubber lists it

MOSS-TTS puts several speech jobs and sound-effect generation in one family. That makes it useful for deciding whether one project covers the voice workflow you need or whether its separate models and setup paths add more complexity than a narrower tool.

Source links

Source materials

Reader note

Before relying on this entry

LifeHubber lists entries to help readers inspect AI projects, not to endorse them or prove they are safe, suitable, accurate, maintained, or right for a specific use. We do not verify every entry in depth. Before relying on anything listed, review the original materials, terms, privacy practices, limits, and risks that matter for your situation.

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