In recent times, deep artificial neural networks have achieved many successes in pattern
recognition. Part of this success can be attributed to the reliance on big data to increase …

This paper presents a speech recognition system that directly transcribes audio data with
text, without requiring an intermediate phonetic representation. The system is based on a …

Visual speech information plays an important role in automatic speech recognition (ASR)
especially when audio is corrupted or even inaccessible. Despite the success of audio …

This paper investigates data augmentation for deep neural network acoustic modeling
based on label-preserving transformations to deal with data sparsity. Two data …

Over the past decade or so, several advances have been made to the design of modern
large vocabulary continuous speech recognition (LVCSR) systems to the point where their …

Augmenting datasets by transforming inputs in a way that does not change the label is a
crucial ingredient of the state of the art methods for object recognition using neural networks …

With the growing impact of information technology on daily life, speech is becoming
increasingly important for providing a natural means of communication between humans …

Lung sounds convey relevant information related to pulmonary disorders, and to evaluate
patients with pulmonary conditions, the physician or the doctor uses the traditional …

An increasing number of human-robot interaction (HRI) studies are now taking place in
applied settings with children. These interactions often hinge on verbal interaction to …

Anonymisation has the goal of manipulating speech signals in order to degrade the
reliability of automatic approaches to speaker recognition, while preserving other aspects of …