GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
General Purpose Audio for ASR, TTS, and Voice Conversion
Good fit when
- When you require an all-in-one performance-oriented solution covering ASR, TTS, and VC tasks in a unified model.
- For deploying edge devices that support ONNX runtime to leverage pre-optimized GPA models.
Avoid when
- If your project demands ultra-specialized performance tailored for only one of the specific audio tasks.
- When real-time requirements are paramount, and you need a lightweight standalone model like GPA-TTS for limited hardware capabilities.
Observed Jul 15, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (117d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- 34 low (34 low)
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install GPASimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
GPA is an all-in-one model for speech recognition, text-to-speech, and voice conversion tasks, offering near-SOTA performance in a unified framework.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Sep 20, 2026
Categories
Tags
README
<div align="center" <img src="scripts/GPA.png" width="80%" alt="GPA Logo"/ GPA: One Model for Speech Recognition, Text to Speech, and Voice Conversion </div <details open <summary <strong 📢 Announcements</strong </summary <div style="max height: 150px; overflow y: auto; border:...
For agents
This page has a .md twin and JSON over the API.