In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

Growth of data eases the way to access the world but requires increasing amounts of energy
to store and process. Neuromorphic electronics has emerged in the last decade, inspired by …

Artificial neural networks (ANN) have become the mainstream acoustic modeling technique
for large vocabulary automatic speech recognition (ASR). A conventional ANN features a …

In response to uncovering brain mechanisms underlying vocal communication and
searching for biomarkers for mental illnesses, speech prosody has been increasingly …

A central challenge for articulatory speech synthesis is the simulation of realistic articulatory
movements, which is critical for the generation of highly natural and intelligible speech. This …

We present a framework for recognizing isolated and continuous American Sign Language
(ASL) sentences from three-dimensional data. The data are obtained by using physics …

Background: Differential diagnosis and treatment planning of developmental speech
disorders (DSD) remains a major challenge in paediatric speech-language pathology …

We bridge the gap between two issues in infant development: vocal development and
intrinsic motivation. We propose and experimentally test the hypothesis that general …

" Description: A definitive reference--now extensively revised with 70% new material--this
book presents cutting-edge knowledge on how learning disorders develop and how to …

This paper reviews the current state of several formal models of speech motor control, with
particular focus on the low-level control of the speech articulators. Further development of …