# An Objective Evaluation Framework for Pathological Speech Synthesis

arXiv: https://arxiv.org/abs/2107.00308 · HTML: https://mlsanity.com/paper/2107.00308/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 28 references that are in the map.
- First posted on arXiv 1 Jul 2021.

## Builds on (most cited first, 2 of 2)

- [Listening while Speaking: Speech Chain by Deep Learning](https://mlsanity.com/paper/1707.04879/) (2017)
- [Improving Dysarthric Speech Intelligibility Using Cycle-consistent Adversarial Training](https://mlsanity.com/paper/2001.04260/) (2020)

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

- [Towards Identity Preserving Normal to Dysarthric Voice Conversion](https://mlsanity.com/paper/2110.08213/) (2021)
- [DuTa-VC: A Duration-aware Typical-to-atypical Voice Conversion Approach with Diffusion Probabilistic Model](https://mlsanity.com/paper/2306.10588/) (2023)
- [Unsupervised Rhythm and Voice Conversion of Dysarthric to Healthy Speech for ASR](https://mlsanity.com/paper/2501.10256/) (2025)
- [Manipulation of oral cancer speech using neural articulatory synthesis](https://mlsanity.com/paper/2203.17072/) (2022)

## Abstract (arXiv)

The development of pathological speech systems is currently hindered by the lack of a standardised objective evaluation framework. In this work, (1) we utilise existing detection and analysis techniques to propose a general framework for the consistent evaluation of synthetic pathological speech. This framework evaluates the voice quality and the intelligibility aspects of speech and is shown to be complementary using our experiments. (2) Using our proposed evaluation framework, we develop and test a dysarthric voice conversion system (VC) using CycleGAN-VC and a PSOLA-based speech rate modification technique. We show that the developed system is able to synthesise dysarthric speech with different levels of speech intelligibility.