AIMC Topic: Speech

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Detecting Alzheimer's Disease from Continuous Speech Using Language Models.

Journal of Alzheimer's disease : JAD
BACKGROUND: Recently, many studies have been carried out to detect Alzheimer's disease (AD) from continuous speech by linguistic analysis and modeling. However, few of them utilize language models (LMs) to extract linguistic features and to investiga...

Fuzzy Classification Methods Based Diagnosis of Parkinson's disease from Speech Test Cases.

Current aging science
BACKGROUND: Together with the Alzheimer's disease, Parkinson's disease is considered as one of the two serious known neurodegenerative diseases. Physicians find it hard to predict whether a given patient has already developed or is expected to develo...

Automatic speech recognition: A primer for speech-language pathology researchers.

International journal of speech-language pathology
Automatic speech recognition (ASR) is increasingly becoming an integral component of our daily lives. This trend is in large part due to recent advances in machine learning, and specifically in deep learning, that have led to accurate ASR across nume...

A review of abstract concept learning in embodied agents and robots.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
This paper reviews computational modelling approaches to the learning of abstract concepts and words in embodied agents such as humanoid robots. This will include a discussion of the learning of abstract words such as 'use' and 'make' in humanoid rob...

Depression Severity Classification from Speech Emotion.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Major Depressive Disorder (MDD) is a common psychiatric illness. Automatically classifying depression severity using audio analysis can help clinical management decisions during Deep Brain Stimulation (DBS) treatment of MDD patients. Leveraging the l...

A Sibling-Mediated Intervention for Children with Autism Spectrum Disorder: Using the Natural Language Paradigm (NLP).

Journal of autism and developmental disorders
We taught three typically developing siblings to occasion speech by implementing the Natural Language Paradigm (NLP) with their brothers with autism spectrum disorder (ASD). A non-concurrent multiple baseline design across children with ASD and sibli...

Inferring imagined speech using EEG signals: a new approach using Riemannian manifold features.

Journal of neural engineering
OBJECTIVE: In this paper, we investigate the suitability of imagined speech for brain-computer interface (BCI) applications.

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms.

Trends in hearing
The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid alg...

[The application of artificial neural network on the assessment of lexical tone production of pediatric cochlear implant users].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
The present study was carried out to explore the tone production ability of the Mandarin-speaking children with cochlear implants (CI) by using an artificial neural network model and to examine the potential contributing factors underlining their to...