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Speech vision: An end-to-end deep learning-based dysarthric automatic speech recognition system
SR Shahamiri - IEEE Transactions on Neural Systems and …, 2021 - ieeexplore.ieee.org
Dysarthria is a disorder that affects an individual's speech intelligibility due to the paralysis of
muscles and organs involved in the articulation process. As the condition is often associated …
muscles and organs involved in the articulation process. As the condition is often associated …
E2E-DASR: End-to-end deep learning-based dysarthric automatic speech recognition
Dysarthria is a motor speech disability caused by weak muscles and organs involved in the
articulation process, thereby affecting the speech intelligibility of individuals. Because this …
articulation process, thereby affecting the speech intelligibility of individuals. Because this …
[HTML][HTML] Recent advancements in automatic disordered speech recognition: A survey paper
N Gohider, OA Basir - Natural Language Processing Journal, 2024 - Elsevier
Abstract Automatic Speech Recognition technology (ASR) has recently witnessed a
paradigm shift with respect to performance accuracy. Nevertheless, impaired speech …
paradigm shift with respect to performance accuracy. Nevertheless, impaired speech …
Distributed intelligence in industrial and automotive cyber–physical systems: a review
Cyber–physical systems (CPSs) are evolving from individual systems to collectives of
systems that collaborate to achieve highly complex goals, realizing a cyber–physical system …
systems that collaborate to achieve highly complex goals, realizing a cyber–physical system …
Data augmentation techniques for transfer learning-based continuous dysarthric speech recognition
Data augmentation is an essential component in building a dysarthric speech recognition
system, as speech data collection from dysarthric speakers with varying degree of disorder …
system, as speech data collection from dysarthric speakers with varying degree of disorder …
Tran-DSR: A hybrid model for dysarthric speech recognition using transformer encoder and ensemble learning
Over the last decade, there has been a notable increase in the pervasiveness of
neurological diseases due to population growth and aging. Among individuals with …
neurological diseases due to population growth and aging. Among individuals with …
[PDF][PDF] Enhancement automatic speech recognition by deep neural networks
The performance of speech recognition tasks utilizing systems based on deep learning has
improved dramatically in recent years by utilizing different deep designs and learning …
improved dramatically in recent years by utilizing different deep designs and learning …
Data augmentation using virtual microphone array synthesis and multi-resolution feature extraction for isolated word dysarthric speech recognition
Dysarthria is a speech-motor disorder that affects the articulatory systems inhibiting their
speech communication efforts. To handle their communication problems, a speech …
speech communication efforts. To handle their communication problems, a speech …
A spatial–temporal graph model for pronunciation feature prediction of Chinese poetry
Q Wang, W Liu, X Wang, X Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the development of artificial intelligence, speech recognition and prediction have
become one of the important research domains with wild applications, such as intelligent …
become one of the important research domains with wild applications, such as intelligent …
Speech Recognition via CTC-CNN Model.
WT Sung, HW Kang, SJ Hsiao - Computers, materials & …, 2023 - search.ebscohost.com
In the speech recognition system, the acoustic model is an important underlying model, and
its accuracy directly affects the performance of the entire system. This paper introduces the …
its accuracy directly affects the performance of the entire system. This paper introduces the …