# Aratako/Irodori-TTS

A Flow Matching-based Text-to-Speech Model with Emoji-driven Style Control

Repository: https://github.com/Aratako/Irodori-TTS
Canonical: https://ross.abutalabs.com/products/irodori-tts
Homepage: https://huggingface.co/collections/Aratako/irodori-tts
Language: Python
License: MIT
License Family: permissive
Topics: diffusion-models, flow-matching, python, speech-synthesis, text-to-speech, tts, voice-cloning
Last push: 2026-08-11T02:20:18+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 97, release rhythm 35, longevity 13
- inputs: {"age_days": 189, "days_push": 23, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1219, forks 151 (observed 2026-08-28T04:04:01.788864+00:00)

## What it is
Irodori-TTS is a Flow Matching-based text-to-speech model with training and inference code, built on a Rectified Flow Diffusion Transformer over DACVAE latents. It supports zero-shot voice cloning, multi-modal voice design with emoji-based style control, LoRA fine-tuning, and CLI/Gradio inference.

## Use cases
- clone a voice from reference audio
- generate speech with emotion and style control
- design a custom voice from text descriptions
- fine-tune a TTS model with LoRA on my own voice
- train a flow matching text-to-speech model
- generate japanese speech from text
- run tts inference from the command line

## When to choose
- you need zero-shot voice cloning or voice design with style/emotion control
- you want to fine-tune or train a modern flow-matching TTS model
- you want emoji-annotated text to influence speech delivery
- you need a compact open TTS model with released checkpoints and demos

## When to avoid
- you need a production-ready OpenAI-compatible serving API out of the box (use the companion Irodori-TTS-Server)
- you need non-Japanese or multilingual TTS
- you have no GPU and need fast low-latency synthesis
- you just want a plug-and-play TTS without touching model code

## Facets
- artifact type: library
- maturity: active
- function: tts, machine-learning, deep-learning, audio-processing, llm-training
- domain: speech-processing, machine-learning
- platform: python, cli, cross-platform
- tags: flow-matching, diffusion-transformer, voice-cloning, voice-design, emoji-style-control, dacvae, lora-fine-tuning, japanese-tts, audio-watermarking, gradio, audio, natural-language-processing, gpu

## Member repositories
- Aratako/Irodori-TTS (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:01.788864+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 2026-08-30T06:16:11.127450+00:00, confidence not recorded.
  - readme: https://github.com/Aratako/Irodori-TTS (fetched 2026-08-28T04:04:01.788864+00:00, sha 67ea56689801)
  - homepage: https://huggingface.co/collections/Aratako/irodori-tts (fetched 2026-08-29T12:24:49.041329+00:00, sha c3d6002da11c)
  - site_page: https://huggingface.co/docs (fetched 2026-08-29T12:24:49.043743+00:00, sha bdec26667b98)
  - site_page: https://huggingface.co/docs/hub/collections (fetched 2026-08-29T12:24:49.047354+00:00, sha 8bc6746b9e69)
  - site_page: https://huggingface.co/pricing (fetched 2026-08-29T12:24:49.045484+00:00, sha de6b7a178be5)
  - site_page: https://huggingface.co/huggingface (fetched 2026-08-29T12:24:49.049023+00:00, sha 6ae0067a4ae4)
- Data as of 2026-08-30T08:39:29.467469+00:00.