LocalClaw/TTS/Index-Echo S2ST 2B
Local speech translation model

Index-Echo S2ST 2B

Catalogue summary: Apache-licensed speech-to-speech translation package for local dubbing. The 2B release translates Chinese or English source speech into English, Spanish, Japanese or Chinese target speech, keeps source-voice conditioning through CosyVoice3, and ships a self-contained Hugging Face package with safetensors, ONNX assets and a documented Python API.

Repository editorial metadata; verify comparative claims in the linked upstream material.

GPU recommendedspeech-to-speech translation and dubbing4 languagesApache 2.0
Choose an app

Start with the recommended app, or choose another supported option.

Compare speech models
Open Index-Echo S2ST 2BNative application and release instructionsOpen in UnslothLaunches Unsloth Desktop on this modelOpen on Hugging FaceFiles, licence and model cardCheck my machineOptional: verify the fit with your saved hardware

Desktop app links require the app to be installed. If nothing opens, LocalClaw will show app-download and model-file fallbacks.

Catalogue quality
9/10
Catalogue speed
7.8/10
Model size
2B translator decoder plus bundled CosyVoice3 assets; 12GB VRAM floor
Voices
Source-voice conditioned speech-to-speech translation

Can Index-Echo S2ST 2B run locally?

Index-Echo S2ST 2B can run locally for speech-to-speech translation and dubbing over supplied recordings. Use the verified setup options on this page; no terminal command is required to choose the right path.

Apache 2.0 license. Still verify upstream usage notes before shipping.

Upstream source
speech-translationmultilingualcloning

Audio profile

Cat. quality
9
Cat. speed
7.8
Audio
8.6

Best fit

Index-Echo S2ST 2B is best for local speech translation, dubbing and voice-conditioned multilingual audio workflows.

Hardware: gpu

Model details

Type
Local speech translation model
Family
index
Latency
medium
Formats
pytorchsafetensorsonnx
Languages
zh, en, es, ja
Context
Six directions: zh->en/es/ja and en->zh/es/ja; 24 kHz output; official DubbingBridgeModel Python API, pinned CUDA/PyTorch environment, bundled CosyVoice3 path and at least 12GB VRAM recommended; CPU inference is unverified upstream

Install locally

01
Check runtimeConfirm the backend supports pytorch, safetensors, onnx on your machine.
02
Open recommended setupUse the app and model links above. LocalClaw does not expose a terminal command.
03
Test locallyRun a short private audio prompt before moving into production workflows.

Good for

  • speech-to-speech translation and dubbing
  • GPU recommended local workflows
  • speech-translation, multilingual, cloning

Watch before shipping

  • Validate pronunciation, latency and artifacts with your own voice samples.
  • Review the upstream license and acceptable-use notes.
  • Benchmark on your target CPU, Apple Silicon or GPU setup.

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