# CjangCjengh/MoeGoe

Executable file for VITS inference

Repository: https://github.com/CjangCjengh/MoeGoe
Canonical: https://ross.abutalabs.com/products/moegoe
Language: Python
License: MIT
License Family: permissive
Last push: 2023-08-22T07:17:37+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1487, "days_push": 1107, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2423, forks 242 (observed 2026-08-28T04:06:50.687874+00:00)

## What it is
MoeGoe is an executable command-line tool for running inference with VITS text-to-speech models, supporting TTS, voice conversion, HuBERT-VITS, and W2V2-VITS with emotional reference audio. It is written in Python and distributed as a ready-to-run executable.

## Use cases
- generate speech audio from text using a VITS model
- convert an audio clip to sound like a different speaker
- run voice conversion with HuBERT-soft features
- synthesize speech with emotion control via a W2V2 emotion model
- batch-generate anime character voice lines locally

## When to choose
- you have a trained VITS model and want a simple offline inference tool
- you need voice conversion between speakers without writing code
- you want a lightweight executable instead of a full ML pipeline

## When to avoid
- you need to train or fine-tune VITS models
- you want a GUI (use the companion MoeGoe_GUI instead)
- you need production-grade streaming TTS APIs

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: tts, speech-recognition, audio-processing, machine-learning, llm-inference
- domain: speech-processing, machine-learning, artificial-intelligence
- platform: windows, cross-platform, python, cli
- tags: vits, voice-conversion, text-to-speech, hubert, inference, anime-voice, audio

## Member repositories
- CjangCjengh/MoeGoe (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:50.687874+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:31:52.266580+00:00, confidence not recorded.
  - readme: https://github.com/CjangCjengh/MoeGoe (fetched 2026-08-28T04:06:50.687874+00:00, sha d53f8408766a)
- Data as of 2026-08-30T08:39:29.467469+00:00.