# EasyCall corpus: a dysarthric speech dataset

arXiv: https://arxiv.org/abs/2104.02542 · HTML: https://mlsanity.com/paper/2104.02542/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 13 references that are in the map.
- First posted on arXiv 6 Apr 2021.

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

- [VoxCeleb2: Deep Speaker Recognition](https://mlsanity.com/paper/1806.05622/) (2018)
- [TED-LIUM 3: twice as much data and corpus repartition for experiments on speaker adaptation](https://mlsanity.com/paper/1805.04699/) (2018)

## Built on by (most cited first, 15 of 15)

- [Cross-lingual Self-Supervised Speech Representations for Improved Dysarthric Speech Recognition](https://mlsanity.com/paper/2204.01670/) (2022)
- [Personalized Adversarial Data Augmentation for Dysarthric and Elderly Speech Recognition](https://mlsanity.com/paper/2205.06445/) (2022)
- [Enhancing Voice Wake-Up for Dysarthria: Mandarin Dysarthria Speech Corpus Release and Customized System Design](https://mlsanity.com/paper/2406.10304/) (2024)
- [PRiSM: Benchmarking Phone Realization in Speech Models](https://mlsanity.com/paper/2601.14046/) (2026)
- [Multilingual Dysarthric Speech Assessment Using Universal Phone Recognition and Language-Specific Phonemic Contrast Modeling](https://mlsanity.com/paper/2601.21205/) (2026)
- [Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource Languages](https://mlsanity.com/paper/2505.14874/) (2025)
- [Latent Phrase Matching for Dysarthric Speech](https://mlsanity.com/paper/2306.05446/) (2023)
- [Generative Adversarial Network based Voice Conversion: Techniques, Challenges, and Recent Advancements](https://mlsanity.com/paper/2504.19197/) (2025)
- [Something from Nothing: Data Augmentation for Robust Severity Level Estimation of Dysarthric Speech](https://mlsanity.com/paper/2603.15988/) (2026)
- [Voice Quality Dimensions as Interpretable Primitives for Speaking Style for Atypical Speech and Affect](https://mlsanity.com/paper/2505.21809/) (2025)
- [Idiosyncratic Versus Normative Modeling of Atypical Speech Recognition: Dysarthric Case Studies](https://mlsanity.com/paper/2509.16718/) (2025)
- [Risk of re-identification for shared clinical speech recordings](https://mlsanity.com/paper/2210.09975/) (2022)
- [Arabic Dysarthric Speech Recognition Using Adversarial and Signal-Based Augmentation](https://mlsanity.com/paper/2306.04368/) (2023)
- [Huntington Disease Automatic Speech Recognition with Biomarker Supervision](https://mlsanity.com/paper/2603.11168/) (2026)
- [Phonological Subspace Collapse Is Aetiology-Specific and Cross-Lingually Stable: Evidence from 3,374 Speakers](https://mlsanity.com/paper/2604.21706/) (2026)

## Abstract (arXiv)

This paper introduces a new dysarthric speech command dataset in Italian, called EasyCall corpus. The dataset consists of 21386 audio recordings from 24 healthy and 31 dysarthric speakers, whose individual degree of speech impairment was assessed by neurologists through the Therapy Outcome Measure. The corpus aims at providing a resource for the development of ASR-based assistive technologies for patients with dysarthria. In particular, it may be exploited to develop a voice-controlled contact application for commercial smartphones, aiming at improving dysarthric patients' ability to communicate with their family and caregivers. Before recording the dataset, participants were administered a survey to evaluate which commands are more likely to be employed by dysarthric individuals in a voice-controlled contact application. In addition, the dataset includes a list of non-commands (i.e., words near/inside commands or phonetically close to commands) that can be leveraged to build a more robust command recognition system. At present commercial ASR systems perform poorly on the EasyCall Corpus as we report in this paper. This result corroborates the need for dysarthric speech corpora for developing effective assistive technologies. To the best of our knowledge, this database represents the richest corpus of dysarthric speech to date.