Deep learning applications in telerehabilitation speech therapy scenarios

D Mulfari, D La Placa, C Rovito, A Celesti… - Computers in Biology and …, 2022 - Elsevier
Nowadays, many application scenarios benefit from automatic speech recognition (ASR)
technology. Within the field of speech therapy, in some cases ASR is exploited in the …

Machine learning assistive application for users with speech disorders

D Mulfari, G Meoni, M Marini, L Fanucci - Applied Soft Computing, 2021 - Elsevier
This paper investigates machine learning approaches toward the development of a speaker
dependent keywords spotting system intended for users with speech disorders, in particular …

Predicting developmental language disorders using artificial intelligence and a speech data analysis tool

EA Beccaluva, F Catania, F Arosio… - Human–Computer …, 2024 - Taylor & Francis
ABSTRACT Developmental Language Disorder (DLD) affects children's comprehension and
production of spoken language without any known biomedical condition. The importance of …

Toward a lightweight ASR solution for atypical speech on the edge

D Mulfari, L Carnevale, M Villari - Future Generation Computer Systems, 2023 - Elsevier
In this article, to the purpose of simplifying challenges in designing automatic speech
recognition (ASR) systems working on disordered speech, we focus on an isolated word …

Automatic Speech and Voice Disorder Detection using Deep Learning-A Systematic Literature Review

I Sindhu, MS Sainin - IEEE Access, 2024 - ieeexplore.ieee.org
Speech and voice disorders are highly prevalent and a significant concern, particularly
among children. These disorders have a notable impact on individual's personalities …

IDEA: an Italian dysarthric speech database

M Marini, M Viganò, M Corbo, M Zettin… - 2021 IEEE Spoken …, 2021 - ieeexplore.ieee.org
This paper describes IDEA a database of Italian dysarthric speech produced by 45 speakers
affected by 8 different pathologies. Neurologic diagnoses were collected from the subjects' …

Exploring ai-based speaker dependent methods in dysarthric speech recognition

D Mulfari, A Celesti, M Villari - 2022 22nd IEEE International …, 2022 - ieeexplore.ieee.org
In this paper, we present our recent improvements within the CapisciAMe project, an Italian
initiative aimed at investigating the usage of deep learning strategies for automatic speech …

Comparison of noise reduction techniques for dysarthric speech recognition

D Mulfari, G Campobello, G Gugliandolo… - 2022 IEEE …, 2022 - ieeexplore.ieee.org
The paper investigates the impact of denoising techniques on a deep learning recognition
system for speak-ers with dysarthria, ie, a neuromotor speech disorder which compromises …

Sequence-to-Sequence Models in Italian Atypical Speech Recognition

D Mulfari, L Carnevale, M Villari - 2024 IEEE Symposium on …, 2024 - ieeexplore.ieee.org
In the domain of automatic speech recognition (ASR), we explore the usage of a state-of-the-
art transformer-based sequence-to-sequence model to build a speaker-dependent isolated …

Device control system based on classified EMG signals: a machine learning approach

AC Barbosa - 2024 - search.proquest.com
In contemporary society, certain physical attributes are celebrated, while others are
stigmatized, leading to barriers in the social inclusion of individuals who do not conform to …