# NeuroVoz: a Castillian Spanish corpus of parkinsonian speech

arXiv: https://arxiv.org/abs/2403.02371 · HTML: https://mlsanity.com/paper/2403.02371/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 68 references that are in the map.
- First posted on arXiv 4 Mar 2024.

## Builds on (most cited first, 1 of 1)

- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)

## Built on by (most cited first, 13 of 13)

- [Unveiling Interpretability in Self-Supervised Speech Representations for Parkinson's Diagnosis](https://mlsanity.com/paper/2412.02006/) (2024)
- [Innovative Speech-Based Deep Learning Approaches for Parkinson's Disease Classification: A Systematic Review](https://mlsanity.com/paper/2407.17844/) (2024)
- [Evaluating the Usefulness of Non-Diagnostic Speech Data for Developing Parkinson's Disease Classifiers](https://mlsanity.com/paper/2505.18722/) (2025)
- [Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data](https://mlsanity.com/paper/2506.02078/) (2025)
- [Something from Nothing: Data Augmentation for Robust Severity Level Estimation of Dysarthric Speech](https://mlsanity.com/paper/2603.15988/) (2026)
- [Training-Free Cross-Lingual Dysarthria Severity Assessment via Phonological Subspace Analysis in Self-Supervised Speech Representations](https://mlsanity.com/paper/2604.10123/) (2026)
- [FiLM-Based Speaker Conditioning of a SpeechLLM for Pathological Speech Recognition](https://mlsanity.com/paper/2606.06211/) (2026)
- [Scenario of Use Scheme: Threat Model Specification for Speaker Privacy Protection in the Medical Domain](https://mlsanity.com/paper/2409.16106/) (2024)
- [Cross-Lingual Multi-Granularity Framework for Interpretable Parkinson's Disease Diagnosis from Speech](https://mlsanity.com/paper/2510.03758/) (2025)
- [Phonological Subspace Collapse Is Aetiology-Specific and Cross-Lingually Stable: Evidence from 3,374 Speakers](https://mlsanity.com/paper/2604.21706/) (2026)
- [A Benchmark for Early-stage Parkinson's Disease Detection from Speech](https://mlsanity.com/paper/2605.14066/) (2026)
- [Zero-Shot Parkinson's Disease Detection from Speech: Comparing Large Audio and Language Models](https://mlsanity.com/paper/2605.24806/) (2026)
- [S-DiverSe: Spanish Diverse Speech](https://mlsanity.com/paper/2607.03207/) (2026)

## Abstract (arXiv)

The screening of Parkinson's Disease (PD) through speech is hindered by a notable lack of publicly available datasets in different languages. This fact limits the reproducibility and further exploration of existing research. To address this gap, this manuscript presents the NeuroVoz corpus consisting of 112 native Castilian-Spanish speakers, including 58 healthy controls and 54 individuals with PD, all recorded in ON state. The corpus showcases a diverse array of speech tasks: sustained vowels; diadochokinetic tests; 16 Listen-and-Repeat utterances; and spontaneous monologues. The dataset is also complemented with subjective assessments of voice quality performed by an expert according to the GRBAS scale (Grade/Roughness/Breathiness/Asthenia/Strain), as well as annotations with a thorough examination of phonation quality, intensity, speed, resonance, intelligibility, and prosody. The corpus offers a substantial resource for the exploration of the impact of PD on speech. This data set has already supported several studies, achieving a benchmark accuracy of 89% for the screening of PD. Despite these advances, the broader challenge of conducting a language-agnostic, cross-corpora analysis of Parkinsonian speech patterns remains open.