Connectionist Speech Recognition
Subtitle: a Hybrid Approach
By: by Hervé A. Bourlard, Nelson Morgan
Contributors: Morgan, Nelson
Series: The Springer International Series in Engineering and Computer Science, VLSI, Computer Architecture and Digital Signal Processing -- 247; Springer International Series in Engineering and Computer Science, VLSI, Computer Architecture and Digital Signal Processing -- 247.
Publisher: Springer US
Published: 1994
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] :
Number of pages: 313
ISBN-13: 9781461364092; 9781461532101
Subjects: Systems engineering; Engineering; Computer engineering
Description: Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.
Notes: Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.