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Speech

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Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria.

The New England journal of medicine
BACKGROUND: Technology to restore the ability to communicate in paralyzed persons who cannot speak has the potential to improve autonomy and quality of life. An approach that decodes words and sentences directly from the cerebral cortical activity of...

Deep Neural Network Driven Speech Classification for Relevance Detection in Automatic Medical Documentation.

Studies in health technology and informatics
The automation of medical documentation is a highly desirable process, especially as it could avert significant temporal and monetary expenses in healthcare. With the help of complex modelling and high computational capability, Automatic Speech Recog...

On training targets for deep learning approaches to clean speech magnitude spectrum estimation.

The Journal of the Acoustical Society of America
Estimation of the clean speech short-time magnitude spectrum (MS) is key for speech enhancement and separation. Moreover, an automatic speech recognition (ASR) system that employs a front-end relies on clean speech MS estimation to remain robust. Tra...

Deep learning approaches for neural decoding across architectures and recording modalities.

Briefings in bioinformatics
Decoding behavior, perception or cognitive state directly from neural signals is critical for brain-computer interface research and an important tool for systems neuroscience. In the last decade, deep learning has become the state-of-the-art method i...

Speech emotion recognition based on transfer learning from the FaceNet framework.

The Journal of the Acoustical Society of America
Speech plays an important role in human-computer emotional interaction. FaceNet used in face recognition achieves great success due to its excellent feature extraction. In this study, we adopt the FaceNet model and improve it for speech emotion recog...

Phonetic variability constrained bottleneck features for joint speaker recognition and physical task stress detection.

The Journal of the Acoustical Society of America
Normalizing intrinsic variabilities (e.g., variability in speech production brought on by aging, physical or cognitive task stress, Lombard effect, etc.) in speech and speaker recognition models is essential for system robustness. This study focuses ...

A systematic literature review of automatic Alzheimer's disease detection from speech and language.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In recent years numerous studies have achieved promising results in Alzheimer's Disease (AD) detection using automatic language processing. We systematically review these articles to understand the effectiveness of this approach, identify ...

Verbal analogy problem sets: An inventory of testing materials.

Behavior research methods
Analogical reasoning is an active topic of investigation across education, artificial intelligence (AI), cognitive psychology, and related fields. In all fields of inquiry, explicit analogy problems provide useful tools for investigating the mechanis...

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

The Journal of the Acoustical Society of America
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...

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
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...