AIMC Topic: Speech

Clear Filters Showing 341 to 350 of 368 articles

A two-stage deep learning algorithm for talker-independent speaker separation in reverberant conditions.

The Journal of the Acoustical Society of America Sep 1, 2020
Speaker separation is a special case of speech separation, in which the mixture signal comprises two or more speakers. Many talker-independent speaker separation methods have been introduced in recent years to address this problem in anechoic conditi...
Deep Learning Speech Speech Perception Algorithms
View on PubMed DOI

Voice Command Recognition Using Biologically Inspired Time-Frequency Representation and Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Voice command is an important interface between human and technology in healthcare, such as for hands-free control of surgical robots and in patient care technology. Voice command recognition can be cast as a speech classification task, where convolu...
Humans Speech Voice Neural Networks, Computer
View on PubMed DOI

Parkinson's Disease Classification using Pitch Synchronous Speech Segments and Fine Gaussian Kernels based SVM.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Researchers have been using signal processing based methods to assess speech from Parkinson's disease (PD) patients and identify the contrasting features in comparison to speech from healthy controls (HC). The methodologies follow conventional approa...
Speech Support Vector Machine Humans Principal Component Analysis Parkinson Disease Algorithms
View on PubMed DOI

Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety.

Journal of the American Medical Informatics Association : JAMIA Jun 1, 2020
OBJECTIVE: The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning algorithms can be used to train a classifier for anxiety.
Algorithms Language Humans Machine Learning Male Middle Aged Anxiety Female Communication Caregivers Proof of Concept Study Speech Family Interviews as Topic
View on PubMed DOI

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition.

Cognitive science Apr 1, 2020
Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-ste...
Speech Models, Neurological Speech Perception Phonetics Semantics Female Male Neural Networks, Computer Computer Simulation Humans
View on PubMed DOI

Artificial Intelligence, Speech, and Language Processing Approaches to Monitoring Alzheimer's Disease: A Systematic Review.

Journal of Alzheimer's disease : JAD Jan 1, 2020
BACKGROUND: Language is a valuable source of clinical information in Alzheimer's disease, as it declines concurrently with neurodegeneration. Consequently, speech and language data have been extensively studied in connection with its diagnosis.
Speech Cognitive Dysfunction Alzheimer Disease Natural Language Processing Artificial Intelligence Machine Learning Humans Disease Progression
View on PubMed DOI

Decoding Speech from Single Trial MEG Signals Using Convolutional Neural Networks and Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Decoding speech directly from the brain has the potential for the development of the next generation, more efficient brain computer interfaces (BCIs) to assist in the communication of patients with locked-in syndrome (fully paralyzed but aware). In t...
Magnetoencephalography Speech Brain-Computer Interfaces Humans Neural Networks, Computer Machine Learning
View on PubMed DOI

A Comparative Study of Features for Acoustic Cough Detection Using Deep Architectures.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Automatic cough detection is key to tracking the condition of patients suffering from tuberculosis. We evaluate various acoustic features for performing cough detection using deep architectures. As most previous studies have adopted features designed...
Hearing Neural Networks, Computer Humans Speech Tuberculosis Cough Acoustics
View on PubMed DOI

Differentiating post-cancer from healthy tongue muscle coordination patterns during speech using deep learning.

The Journal of the Acoustical Society of America May 1, 2019
The ability to differentiate post-cancer from healthy tongue muscle coordination patterns is necessary for the advancement of speech motor control theories and for the development of therapeutic and rehabilitative strategies. A deep learning approach...
Magnetic Resonance Imaging Neural Networks, Computer Tongue Humans Movement Neoplasms Deep Learning Facial Muscles Speech
View on PubMed DOI

Live human-robot interactive public demonstrations with automatic emotion and personality prediction.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences Apr 29, 2019
Communication with humans is a multi-faceted phenomenon where the emotions, personality and non-verbal behaviours, as well as the verbal behaviours, play a significant role, and human-robot interaction (HRI) technologies should respect this complexit...
Robotics Facial Expression Personality Humans Emotions Speech
View on PubMed DOI
Popular Topics
Recent Journals