sherpa-onnx-tts

Convert text to speech locally using sherpa-onnx across darwin, linux, and win32.

Updated Feb 13, 2026
One-click install
npx skills add https://github.com/jonnytacos8/closed_claw --skill sherpa-onnx-tts-jonnytacos8
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sherpa-onnx-tts
Source: https://github.com/jonnytacos8/closed_claw/tree/main/skills/sherpa-onnx-tts
Command: npx skills add https://github.com/jonnytacos8/closed_claw --skill sherpa-onnx-tts-jonnytacos8

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Local text-to-speech processing entirely offline, enabling voice output without cloud services or network dependency.

Core Features & Use Cases

  • Offline TTS with sherpa-onnx runtime and optional voice models.
  • Cross-platform compatibility (darwin, linux, win32) for embedded assistants, accessibility tools, and demos.
  • Use Case: Build an on-device assistant that reads text aloud without sending data to the cloud.

Quick Start

Activate sherpa-onnx-tts by pointing to a runtime directory and a model directory to generate an audio file from text.

Frequently Asked Questions about sherpa-onnx-tts

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

FAQPage Schema
How do I convert text to speech locally without a cloud network dependency?

To convert text to speech locally without a cloud network dependency, you can use the offline sherpa-onnx runtime to process text and generate audio files entirely on your device without sending data to external servers.

Does offline TTS with sherpa-onnx support cross-platform environments like Windows and Linux?

Offline TTS with sherpa-onnx supports cross-platform environments including Windows, Linux, and macOS, allowing you to build on-device assistants or accessibility tools across different operating systems.

How do I configure sherpa-onnx text-to-speech to generate audio from text?

To configure sherpa-onnx text-to-speech, you must specify a runtime directory and a model directory, which validates required files and enforces environment path configurations to perform audio generation successfully.

What is the best way to build an on-device assistant that reads text aloud offline?

The best way to build an on-device assistant that reads text aloud offline is using local text-to-speech processing with sherpa-onnx, which handles voice output generation without requiring cloud services.

Do I need to download voice models separately for local text-to-speech processing?

For local text-to-speech processing, you need optional voice models placed in a designated model directory, as the sherpa-onnx runtime requires these paths to validate files and execute TTS generation.