# wenet-e2e/speech-synthesis-paper

List of speech synthesis papers.

Repository: https://github.com/wenet-e2e/speech-synthesis-paper
Canonical: https://ross.abutalabs.com/products/speech-synthesis-paper
License: MIT
License Family: permissive
Last push: 2023-07-24T06:46:12+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2214, "days_push": 1136, "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 1074, forks 121 (observed 2026-08-28T04:03:29.040454+00:00)

## What it is
A curated list of speech synthesis (TTS) research papers organized by topic, including acoustic models, vocoders, voice conversion, and singing synthesis. It highlights highly-cited papers to help beginners build foundational knowledge of deep-learning-based TTS.

## Use cases
- find text-to-speech research papers
- learn about deep learning TTS models
- find papers on vocoders and acoustic models
- research voice conversion techniques
- find singing voice synthesis papers
- get started with speech synthesis literature

## When to choose
- you want a curated, categorized reading list for TTS research
- you are a beginner looking for highly-cited foundational papers
- you need references spanning vocoders, voice conversion, and singing synthesis

## When to avoid
- you need runnable code or a software library
- you want speech recognition rather than synthesis papers
- you need up-to-the-minute papers, as the list was last updated in 2023

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: tts, speech-recognition
- domain: speech-processing, machine-learning, tutorials
- platform: cross-platform
- tags: awesome-list, papers, text-to-speech, voice-conversion, vocoder, research, natural-language-processing

## Member repositories
- wenet-e2e/speech-synthesis-paper (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:29.040454+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 2026-08-30T06:53:34.121770+00:00, confidence not recorded.
  - readme: https://github.com/wenet-e2e/speech-synthesis-paper (fetched 2026-08-28T04:03:29.040454+00:00, sha febe31b97f59)
- Data as of 2026-08-30T08:39:29.467469+00:00.