sherpa-onnx-tts

Synthesize speech audio locally from text using sherpa-onnx.

Updated Apr 24, 2026
One-click install
npx skills add https://github.com/frankhli843/gemmahermes --skill sherpa-onnx-tts-frankhli843
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sherpa-onnx-tts
Source: https://github.com/frankhli843/gemmahermes/tree/main/skills/sherpa-onnx-tts
Command: npx skills add https://github.com/frankhli843/gemmahermes --skill sherpa-onnx-tts-frankhli843

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Local text-to-speech synthesis is performed offline without cloud services, ensuring privacy and low latency.

Core Features & Use Cases

  • Local, offline TTS using the sherpa-onnx runtime and models.
  • Cross-platform compatibility (macOS, Linux, Windows) with environment variables for runtime and model directories.
  • Use cases include embedding TTS in desktop apps, voice-enabled assistants, and offline data labeling pipelines.

Quick Start

Run the sherpa-onnx-tts wrapper with your text to generate speech audio.

Frequently Asked Questions about sherpa-onnx-tts

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run offline text-to-speech synthesis locally without cloud services?▼

To run offline text-to-speech synthesis locally, use a CLI wrapper that processes input text to generate speech audio without relying on cloud connectivity. This method guarantees privacy and low latency for your applications.

What environment variables do I need to set for local TTS using sherpa-onnx?▼

Local TTS using sherpa-onnx requires setting the SHERPA_ONNX_RUNTIME_DIR and SHERPA_ONNX_MODEL_DIR environment variables. These directories point the wrapper to the necessary runtime files and pre-trained models for audio synthesis.

Can I use offline TTS across macOS, Linux, and Windows?▼

Yes, offline TTS supports cross-platform compatibility across macOS, Linux, and Windows. You can embed local text-to-speech synthesis into desktop applications and offline data labeling pipelines on any of these operating systems.

Does offline text-to-speech work for embedding voice-enabled assistants in desktop apps?▼

Offline text-to-speech is suitable for embedding voice-enabled assistants in desktop apps. It synthesizes speech locally, removing cloud dependencies and ensuring low latency responses for real-time user interactions.

What is the best way to generate speech audio from text for offline data labeling pipelines?▼

The best way to generate speech audio for offline data labeling pipelines is using a local TTS CLI wrapper. It processes text inputs into audio outputs locally, enabling high-throughput, automated voice generation without external API calls.

Why use local text-to-speech instead of cloud-based TTS APIs?▼

Local text-to-speech is used instead of cloud-based APIs to ensure complete data privacy and low latency. By running inference offline within your own environment, you avoid network delays and external data transmission risks.