# Good practices for evaluation of synthesized speech

arXiv: https://arxiv.org/abs/2503.03250 · HTML: https://mlsanity.com/paper/2503.03250/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Mar 2025.

## Built on by (most cited first, 4 of 4)

- [Analyzing and Improving Speaker Similarity Assessment for Speech Synthesis](https://mlsanity.com/paper/2507.02176/) (2025)
- [The Limits of Reference-Free Speech Quality Metrics as Evaluators and Rewards on Modern Text-to-Speech](https://mlsanity.com/paper/2609.13150/) (2026)
- [An Evaluation Framework for Text-to-Speech Voice Reconstruction](https://mlsanity.com/paper/2606.21343/) (2026)
- [I Hear, Therefore I Trust: A Socio-Technical Investigation of Humans as Synthetic Speech Detectors](https://mlsanity.com/paper/2605.28064/) (2026)

## Abstract (arXiv)

This document is provided as a guideline for reviewers of papers about speech synthesis. We outline some best practices and common pitfalls for papers about speech synthesis, with a particular focus on evaluation. We also recommend that reviewers check the guidelines for authors written in the paper kit and consider those as reviewing criteria as well. This is intended to be a living document, and it will be updated as we receive comments and feedback from readers. We note that this document is meant to provide guidance only, and that reviewers should ultimately use their own discretion when evaluating papers.