AIMC Topic: Speech

Clear Filters Showing 281 to 290 of 395 articles

Biometric identification of listener identity from frequency following responses to speech.

Journal of neural engineering
OBJECTIVE: We investigate the biometric specificity of the frequency following response (FFR), an EEG marker of early auditory processing that reflects phase-locked activity from neural ensembles in the auditory cortex and subcortex (Chandrasekaran a...

HypernasalityNet: Deep recurrent neural network for automatic hypernasality detection.

International journal of medical informatics
BACKGROUND: Cleft palate patients have inability to produce adequate velopharyngeal closure, which results in hypernasal speech. In clinic, hypernasal speech is assessed through subject assessment by speech language pathologists. Automatic hypernasal...

Machine learning in the clinical and language characterisation of primary progressive aphasia variants.

Cortex; a journal devoted to the study of the nervous system and behavior
INTRODUCTION: Primary progressive aphasia (PPA) is a clinical syndrome of neurodegenerative origin with 3 main variants: non-fluent, semantic, and logopenic. However, there is some controversy about the existence of additional subtypes. Our aim was t...

Giving Voice to Vulnerable Children: Machine Learning Analysis of Speech Detects Anxiety and Depression in Early Childhood.

IEEE journal of biomedical and health informatics
Childhood anxiety and depression often go undiagnosed. If left untreated these conditions, collectively known as internalizing disorders, are associated with long-term negative outcomes including substance abuse and increased risk for suicide. This p...

Speech synthesis from neural decoding of spoken sentences.

Nature
Technology that translates neural activity into speech would be transformative for people who are unable to communicate as a result of neurological impairments. Decoding speech from neural activity is challenging because speaking requires very precis...

A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records.

BMC medical informatics and decision making
BACKGROUND: The Named Entity Recognition (NER) task as a key step in the extraction of health information, has encountered many challenges in Chinese Electronic Medical Records (EMRs). Firstly, the casual use of Chinese abbreviations and doctors' per...

A fine-grained Chinese word segmentation and part-of-speech tagging corpus for clinical text.

BMC medical informatics and decision making
BACKGROUND: Chinese word segmentation (CWS) and part-of-speech (POS) tagging are two fundamental tasks of Chinese text processing. They are usually preliminary steps for lots of Chinese natural language processing (NLP) tasks. There have been a large...

Speech synthesis from ECoG using densely connected 3D convolutional neural networks.

Journal of neural engineering
OBJECTIVE: Direct synthesis of speech from neural signals could provide a fast and natural way of communication to people with neurological diseases. Invasively-measured brain activity (electrocorticography; ECoG) supplies the necessary temporal and ...

Machine learning for MEG during speech tasks.

Scientific reports
We consider whether a deep neural network trained with raw MEG data can be used to predict the age of children performing a verb-generation task, a monosyllable speech-elicitation task, and a multi-syllabic speech-elicitation task. Furthermore, we ar...

Improved model adaptation approach for recognition of reduced-frame-rate continuous speech.

PloS one
In distributed speech recognition applications, the front-end device that stands for any handheld electronic device like smartphones and personal digital assistants (PDAs) captures the speech signal, extracts the speech features, and then sends the s...