---
title: SemBridge — Speech & Singing
emoji: 🎤
colorFrom: indigo
colorTo: green
sdk: gradio
sdk_version: 6.30.0
app_file: app.py
short_description: Unified TTS, singing, and mixed speech+song generation
python_version: "3.10"
startup_duration_timeout: 1h
---

# SemBridge — Speech & Singing, one continuous voice

Demo for [ASLP-lab/SemBridge](https://huggingface.co/ASLP-lab/SemBridge) —
**Sem**antic **T**oken Anchoring for **B**ridging discrete semantic supervision and
continuous acoustic generation. The unified model performs **text-to-speech**,
**note-conditioned singing (SVS)**, and **mixed speech+singing** with one
reference voice, in English and Chinese.

- **Tab 🗣️ Text to Speech** — type a sentence, choose a packaged reference voice
  (or upload your own recording + transcript), and listen.
- **Tab 🎵 Singing** — enter a score as `lyric|pitch|duration_seconds` lines and
  render it with a sung reference voice.
- **Tab 🎭 Mixed** — run one of the paper's official speech → singing → speech
  sequences end to end.

Everything runs the authors' own `sembridge` inference package (bundled in this
Space) against the released checkpoint: 64-D 25 Hz continuous latents, 2-frame
patches, BigVGAN-Large / native causal decoding, 44.1 kHz mono WAV output, capped
at 500 patches (40 s) per request.

The ten packaged voices and the singing scores are the exact inputs from the
official [demo page](https://tiamojames.github.io/SemBridge_Demo/) — Seed-TTS
speech references and GTSinger / Opencpop sung references. Those assets retain
their original rights and terms.

## Technical notes

- ZeroGPU (`zero-a10g`), bf16, ~817M-parameter generator + 740M acoustic codecs.
- `@spaces.GPU(duration=…)` uses a callable estimator so each request reserves
  GPU time based on its expected length (flow steps × patch count) instead of a
  flat worst case.
- Reference audio is downmixed and resampled to 44.1 kHz automatically; provide
  ~4–10 s of clean audio plus its exact transcript.