Multitask Learning is an approach to inductive transfer that improves generalization by using
the domain information contained in the training signals of related tasks as an inductive bias …

This paper reviews research on combining artificial neural nets, and provides an overview
of, and an introduction to, the papers contained in this special issue, and its companion …

A large-scale Japanese speech database has been described. The database basically
consists of (1) a word speech database,(2) a continuous speech database,(3) a database for …

Multi-class pattern classification has many applications including text document
classification, speech recognition, object recognition, etc. Multi-class pattern classification …

Several strategies are described that overcome limitations of basic network models as steps
towards the design of large connectionist speech recognition systems. The two major areas …

The rate of convergence of net output error is very low when training feedforward neural
networks for multiclass problems using the backpropagation algorithm. While …

A touted advantage of symbolic representations is the ease of transferring learned
information from one intelligent agent to another. This paper investigates an analogous …

This thesis examines how artificial neural networks can benefit a large vocabulary, speaker
independent, continuous speech recognition system. Currently, most speech recognition …

In spite of the advances accomplished throughout the last decades, automatic speech
recognition (ASR) is still a challenging and difficult task. In particular, recognition systems …

Automatic credit scoring, a crucial risk management tool for banks and financial institutes,
has attracted much attention in the past few decades. As such, various approaches have …