Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review

J Zhang, J Wu, Y Qiu, A Song, W Li, X Li… - Computers in Biology and …, 2023 - Elsevier
The growing and aging of the world population have driven the shortage of medical
resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid …

Assessment of speech intelligibility in Parkinson's disease using a speech-to-text system

G Dimauro, V Di Nicola, V Bevilacqua, D Caivano… - IEEE …, 2017 - ieeexplore.ieee.org
Patients with Parkinson's disease (PD) may have difficulties in speaking because of reduced
coordination of the muscles that control breathing, phonation, articulation, and prosody …

Speaker-independent silent speech recognition from flesh-point articulatory movements using an LSTM neural network

M Kim, B Cao, T Mau, J Wang - IEEE/ACM transactions on …, 2017 - ieeexplore.ieee.org
Silent speech recognition (SSR) converts nonaudio information such as articulatory
movements into text. SSR has the potential to enable persons with laryngectomy to …

Automatic assessment of sentence-level dysarthria intelligibility using BLSTM

C Bhat, H Strik - IEEE Journal of Selected Topics in Signal …, 2020 - ieeexplore.ieee.org
Dysarthria is a motor speech impairment, often characterized by slow and slurred speech
that is generally incomprehensible by human listeners. An understanding of the intelligibility …

Investigation of different time-frequency representations for intelligibility assessment of dysarthric speech

HM Chandrashekar, V Karjigi… - Ieee transactions on …, 2020 - ieeexplore.ieee.org
Speech disorders linked to neurological problems affect person's ability to communicate
through speech. Dysarthria is one of the speech disorders caused due to muscle weakness …

Exploring the Role of Machine Learning in Diagnosing and Treating Speech Disorders: A Systematic Literature Review

Z Brahmi, M Mahyoob, M Al-Sarem… - Psychology Research …, 2024 - Taylor & Francis
Purpose Speech disorders profoundly impact the overall quality of life by impeding social
operations and hindering effective communication. This study addresses the gap in …

Regularized speaker adaptation of KL-HMM for dysarthric speech recognition

M Kim, Y Kim, J Yoo, J Wang… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
This paper addresses the problem of recognizing the speech uttered by patients with
dysarthria, which is a motor speech disorder impeding the physical production of speech …

[PDF][PDF] Acoustic correlates of speech intelligibility. The usability of the eGeMAPS feature set for atypical speech

W Xue, C Cucchiarini, R van Hout, H Strik - 2019 - repository.ubn.ru.nl
Although speech intelligibility has been studied in different fields such as speech pathology,
language learning, psycholinguistics, and speech synthesis, it is still unclear which concrete …

Utterance verification-based dysarthric speech intelligibility assessment using phonetic posterior features

J Fritsch, M Magimai-Doss - Ieee signal processing letters, 2021 - ieeexplore.ieee.org
In the literature, the task of dysarthric speech intelligibility assessment has been approached
through development of different low-level feature representations, subspace modeling …

Analytic phase features for dysarthric speech detection and intelligibility assessment

K Gurugubelli, AK Vuppala - Speech Communication, 2020 - Elsevier
The objectives of the dysarthria assessment are to discriminate dysarthric speech from
normal speech, to estimate the severity of dysarthria in terms of the dysarthric speech …