A survey of automatic speech recognition for dysarthric speech
Z Qian, K ** review
Background More than 80% of people living with Amyotrophic Lateral Sclerosis (plwALS)
develop difficulties with their speech, affecting communication, self-identity and quality of life …
develop difficulties with their speech, affecting communication, self-identity and quality of life …
Residual neural network precisely quantifies dysarthria severity-level based on short-duration speech segments
Recently, we have witnessed Deep Learning methodologies gaining significant attention for
severity-based classification of dysarthric speech. Detecting dysarthria, quantifying its …
severity-based classification of dysarthric speech. Detecting dysarthria, quantifying its …
Speaker adaptation using spectro-temporal deep features for dysarthric and elderly speech recognition
Despite the rapid progress of automatic speech recognition (ASR) technologies targeting
normal speech in recent decades, accurate recognition of dysarthric and elderly speech …
normal speech in recent decades, accurate recognition of dysarthric and elderly speech …
Dysarthria severity assessment using squeeze-and-excitation networks
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 …
progress, and can improve the performance of dysarthric speech recognition systems. In this …
Self-supervised asr models and features for dysarthric and elderly speech recognition
Self-supervised learning (SSL) based speech foundation models have been applied to a
wide range of ASR tasks. However, their application to dysarthric and elderly speech via …
wide range of ASR tasks. However, their application to dysarthric and elderly speech via …
Automated dysarthria severity classification using deep learning frameworks
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 …
proportional to its severity. Assessing the severity level of dysarthria, apart from being a …
Synthesizing dysarthric speech using multi-speaker tts for dysarthric speech recognition
Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility
through slow, uncoordinated control of speech production muscles. Automatic Speech …
through slow, uncoordinated control of speech production muscles. Automatic Speech …
Acoustic modelling from raw source and filter components for dysarthric speech recognition
Acoustic modelling for automatic dysarthric speech recognition (ADSR) is a challenging
task. Data deficiency is a major problem and substantial differences between typical and …
task. Data deficiency is a major problem and substantial differences between typical and …
One-dimensional convolutional neural network and hybrid deep-learning paradigm for classification of specific language impaired children using their speech
Background and objective Screening children for communicational disorders such as
specific language impairment (SLI) is always challenging as it requires clinicians to follow a …
specific language impairment (SLI) is always challenging as it requires clinicians to follow a …