Hey ASR system! Why aren't you more inclusive? Automatic speech recognition systems' bias and proposed bias mitigation techniques. A literature review

MK Ngueajio, G Washington - International Conference on Human …, 2022 - Springer
Speech is the fundamental means of communication between humans. The advent of AI and
sophisticated speech technologies have led to the rapid proliferation of human to computer …

Characterizing dysarthria diversity for automatic speech recognition: A tutorial from the clinical perspective

HP Rowe, SE Gutz, MF Maffei, K Tomanek… - Frontiers in computer …, 2022 - frontiersin.org
Despite significant advancements in automatic speech recognition (ASR) technology, even
the best performing ASR systems are inadequate for speakers with impaired speech. This …

Automated dysarthria severity classification: A study on acoustic features and deep learning techniques

AA Joshy, R Rajan - IEEE Transactions on Neural Systems and …, 2022 - ieeexplore.ieee.org
Assessing the severity level of dysarthria can provide an insight into the patient's
improvement, assist pathologists to plan therapy, and aid automatic dysarthric speech …

[PDF][PDF] Automatic Speech Recognition of Disordered Speech: Personalized Models Outperforming Human Listeners on Short Phrases.

JR Green, RL MacDonald, PP Jiang, J Cattiau… - Interspeech, 2021 - researchgate.net
This study evaluated the accuracy of personalized automatic speech recognition (ASR) for
recognizing disordered speech from a large cohort of individuals with a wide range of …

Speaker adaptation using spectro-temporal deep features for dysarthric and elderly speech recognition

M Geng, X Xie, Z Ye, T Wang, G Li, S Hu… - … on Audio, Speech …, 2022 - ieeexplore.ieee.org
Despite the rapid progress of automatic speech recognition (ASR) technologies targeting
normal speech in recent decades, accurate recognition of dysarthric and elderly speech …

Dysarthria severity assessment using squeeze-and-excitation networks

AA Joshy, R Rajan - Biomedical Signal Processing and Control, 2023 - Elsevier
Automated dysarthria severity identification can aid clinicians in monitoring the patient's
progress, and can improve the performance of dysarthric speech recognition systems. In this …

Automated dysarthria severity classification using deep learning frameworks

AA Joshy, R Rajan - 2020 28th European Signal Processing …, 2021 - ieeexplore.ieee.org
Dysarthria is a neuro-motor speech disorder that renders speech unintelligible, in
proportional to its severity. Assessing the severity level of dysarthria, apart from being a …

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 …

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 …

Detection of amyotrophic lateral sclerosis (ALS) via acoustic analysis

R Norel, M Pietrowicz, C Agurto, S Rishoni, G Cecchi - bioRxiv, 2018 - biorxiv.org
ABSTRACT ALS is a fatal neurodegenerative disease with no cure. Experts typically
measure disease progression via the ALSFRS-R score, which includes measurements of …