# sh-lee-prml/HierSpeechpp

The official implementation of HierSpeech++

Repository: https://github.com/sh-lee-prml/HierSpeechpp
Canonical: https://ross.abutalabs.com/products/hierspeechpp
Language: Python
License: MIT
License Family: permissive
Last push: 2024-02-20T05:13:28+00:00

## Health v2 (maintenance only)
Score: 28/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 79
- inputs: {"age_days": 1115, "days_push": 925, "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 1238, forks 152 (observed 2026-08-28T04:04:05.493685+00:00)

## What it is
Official PyTorch implementation of HierSpeech++, a fast zero-shot speech synthesizer for text-to-speech and voice conversion based on hierarchical variational inference. It includes pre-trained models, a text-to-vec framework, and a speech super-resolution module (16 kHz to 48 kHz).

## Use cases
- synthesize speech from text in a zero-shot setting
- clone a voice from a short reference audio prompt
- convert one speaker's voice to another
- upsample 16 kHz speech to 48 kHz
- run a demo TTS model on HuggingFace Spaces

## When to choose
- you need fast, robust zero-shot TTS without LLM-based autoregressive inference
- you want voice conversion with high speaker similarity
- you need human-level quality speech synthesis with pre-trained checkpoints

## When to avoid
- you need a production-ready TTS service with an API
- you need training scripts that are not yet released
- you work outside Python/PyTorch environments

## Facets
- artifact type: library
- maturity: active
- function: tts, speech-recognition, machine-learning, deep-learning
- domain: speech-processing, artificial-intelligence, machine-learning
- platform: python
- tags: zero-shot-tts, voice-conversion, pytorch, speech-synthesis, variational-autoencoder, speech-super-resolution, gpu

## Member repositories
- sh-lee-prml/HierSpeechpp (main) score 28

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:05.493685+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 2026-08-30T08:21:48.745750+00:00, confidence not recorded.
  - readme: https://github.com/sh-lee-prml/HierSpeechpp (fetched 2026-08-28T04:04:05.493685+00:00, sha 4fb1475918af)
- Data as of 2026-08-30T08:39:29.467469+00:00.