# CSTR-Edinburgh/merlin

This is now the official location of the Merlin project.

Repository: https://github.com/CSTR-Edinburgh/merlin
Canonical: https://ross.abutalabs.com/products/cstr-edinburgh-merlin
Homepage: http://www.cstr.ed.ac.uk/projects/merlin/
Language: Python
License: Apache-2.0
License Family: permissive
Topics: merlin, speech-synthesis, text-to-speech, voice-conversion, deep-learning, python, theano, tensorflow, keras
Last push: 2020-03-03T10:46:34+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": 3675, "days_push": 2374, "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 1321, forks 431 (observed 2026-08-28T04:04:21.875859+00:00)

## What it is
Merlin is a toolkit from the University of Edinburgh's CSTR for building deep neural network models for statistical parametric speech synthesis (text-to-speech) and voice conversion. It is written in Python (Theano-based, with optional TensorFlow/Keras support) and ships Kaldi-style recipes, requiring an external text-processing front-end and vocoder.

## Use cases
- build a neural network text-to-speech voice
- train a statistical parametric speech synthesis model
- create a custom voice from my own recordings
- do research on deep learning for speech synthesis
- convert one voice to another with voice conversion
- run a demo TTS voice like slt_arctic

## When to choose
- you need a proven, research-grade DNN-based TTS training toolkit with recipes
- you want an Apache-2.0 licensed system for academic or commercial speech synthesis research
- you are following tutorials or coursework on neural TTS voice building

## When to avoid
- you need a modern, actively maintained framework - development has stalled and it relies on the legacy Theano library
- you want a plug-and-play TTS API rather than training your own models
- you need Windows support - it targets UNIX-like systems

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, speech-recognition, tts, audio-processing
- domain: speech-processing, machine-learning, deep-learning
- platform: python, cross-platform
- tags: text-to-speech, speech-synthesis, voice-conversion, theano, statistical-parametric-synthesis, vocoder, kaldi-style-recipes, audio, linux

## Member repositories
- CSTR-Edinburgh/merlin (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:21.875859+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 2026-08-30T04:47:15.804417+00:00, confidence not recorded.
  - readme: https://github.com/CSTR-Edinburgh/merlin (fetched 2026-08-28T04:04:21.875859+00:00, sha bb645d6da070)
  - homepage: http://www.cstr.ed.ac.uk/projects/merlin/ (fetched 2026-08-29T12:06:12.607157+00:00, sha e9455c7943ae)
- Data as of 2026-08-30T08:39:29.467469+00:00.