
Neural Networks for Vision, Speech and Natural Language
Chapman and Hall (Publisher)
1st Edition
Published on 31. March 1992
Book
Hardback
XII, 442 pages
978-0-412-43000-8 (ISBN)
Article exhausted; check different version
Description
This book is a collection of papers by British Telecom researchers and their BT funded academic collaborators in the BT Connex project. This project concerns the application of neural networks to image processing, speech technology and natural language processing.
Reviews / Votes
`. admirably clearly written, and well structured throughout.The book succeeds very well in its aims: it does improve on the weaknesses of comparisons between approaches in the literature; it implicitly sets out how industrially oriented research is best carried out; and it presents some interesting, sometimes fascinating new results and approaches.' Network 3 `This volume collects the more successful case studies from a very large research project at BT Laboratories that set out to investigate the applicability of neural computing to speech, vision and the natural language problems in this application context.of interest to researchers with specialist knowledge of these subjects or, especially, to those with an interest in the application of multi-layer perceptions to practical problems.' ComputingMore details
Series
Edition
1., 992
Language
English
Place of publication
London
United Kingdom
Target group
Professional and scholarly
Research
Product notice
sewn/stitched
Cloth over boards
Illustrations
XII, 442 p.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 31 mm
Weight
852 gr
ISBN-13
978-0-412-43000-8 (9780412430008)
DOI
10.1007/978-94-011-2360-0
Schweitzer Classification
Other editions
Additional editions

R. Linggard | D.J. Myers | C. Nightingale
Neural Networks for Vision, Speech and Natural Language
E-Book
12/2012
Springer
€96.29
Available for download

R. Linggard | D.J. Myers | C. Nightingale
Neural Networks for Vision, Speech and Natural Language
Book
11/2012
Springer
€106.99
Shipment within 15-20 days
Content
Introduction; Vision; Neural Networks for Vision: an introduction; Image feature location in multiresolution images using a hierarchy of multilayer perceptrons; Training multilayer perceptrons for facial feature location: a case study; The detection of eyes in facial images using radial basis functions; Training and testing of neural net window operators on spatiotemporal images; A neural network feature detector using a multi-resolution pyramid; Image classification using Gabor representation.Speech; Neural Networks for speech processing: an introduction; Spoken alphabet recognition using multilayer perceptrons; Speaker independent vowel recognition; Dissection of perceptron structures in speech and speaker recognition; Segmental subword unit classification using a multilayer perceptron; Natural language; Connectionist natural language processing: an introduction; A single layer higher-order nueral net and its application to context-free grammer recognition; Functional compositionality and soft preference rules; Application of multilayer perceptrons in text-to-speech synthesis systems. Implementation; Hardware imlementation of neural networks: an introduction; Finite word length MLPs; A VLSI architecture for implementing neural networks with on chip back-propagation learning; An opto-electronic neural network processor; Architecture; Architecture: an introduction; A dynamic topology net; The stochastic search network; Node sequence networks; Some dynamical properties of neural networks. Index.