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Speech

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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...

A Two-Step Neural Dialog State Tracker for Task-Oriented Dialog Processing.

Computational intelligence and neuroscience
Dialog state tracking in a spoken dialog system is the task that tracks the flow of a dialog and identifies accurately what a user wants from the utterance. Since the success of a dialog is influenced by the ability of the system to catch the require...

Classification of Overt and Covert Speech for Near-Infrared Spectroscopy-Based Brain Computer Interface.

Sensors (Basel, Switzerland)
People suffering from neuromuscular disorders such as locked-in syndrome (LIS) are left in a paralyzed state with preserved awareness and cognition. In this study, it was hypothesized that changes in local hemodynamic activity, due to the activation ...

Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach.

IEEE journal of biomedical and health informatics
Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Particularly, difficulties to start/stop movements have been observed in patients. From a technical/diagnostic point of view, these movement changes can...

Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning.

Methods (San Diego, Calif.)
Due to the complex and intricate nature associated with their production, the acoustic-prosodic properties of a speech signal are modulated with a range of health related effects. There is an active and growing area of machine learning research in th...

Design of deep echo state networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we provide a novel approach to the architectural design of deep Recurrent Neural Networks using signal frequency analysis. In particular, focusing on the Reservoir Computing framework and inspired by the principles related to the inher...

Confidence in uncertainty: Error cost and commitment in early speech hypotheses.

PloS one
Interactions with artificial agents often lack immediacy because agents respond slower than their users expect. Automatic speech recognisers introduce this delay by analysing a user's utterance only after it has been completed. Early, uncertain hypot...