Piper Text-to-Speech

About

Piper Text-to-Speech enables the generation of high-quality audio from text files and Markdown documents using a privacy-respecting, local neural synthesis engine. It includes a specialized preprocessing script for Obsidian files that strips out frontmatter and formatting, ensuring clear narration of technical content. Users can fine-tune the audio output through speed, volume, and pause duration controls, and even follow guided workflows to incorporate image descriptions into the audio stream. This skill is perfect for turning documentation into listenable content or building accessible workflows without relying on external cloud APIs.

Key Features

• Granular speech control including speed multipliers, volume, and sentence pauses
• Specialized cleaning script for Obsidian markdown to remove frontmatter and formatting
• Batch processing capabilities for converting multiple files simultaneously
• Integrated workflow for transcribing image content into the audio narration
• Local neural text-to-speech synthesis using high-quality ONNX voice models
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Use Cases

• Transforming technical documentation and personal notes into audio narrations for offline listening
• Creating accessible content by narrating visual elements and diagrams through manual transcription integration
• Automating text-to-audio conversion for large datasets of text files or articles