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Connectionist Speech Recognition : a Hybrid Approach

Author: Hervé A Bourlard; Nelson Morgan
Publisher: Boston, MA : Springer US, 1994.
Series: Springer International Series in Engineering and Computer Science, VLSI, Computer Architecture and Digital Signal Processing, 247.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Hervé A Bourlard; Nelson Morgan
ISBN: 9781461532101 1461532108
OCLC Number: 851741558
Description: 1 online resource (xxix, 313 pages).
Contents: 1 Introduction --
2 Statistical Pattern Classification --
3 Hidden Markov Models --
4 Multilayer Perceptrons --
5 Speech Recognition Using ANNs --
6 Statistical Inference in MLPs --
7 The Hybrid HMM/MLP Approach --
8 Experimental Systems --
9 Context-Dependent MLPs --
10 System Tradeoffs --
11 Training Hardware and Software --
12 Cross-Validation In Mlp Training --
13 Hmm/Mlp And Predictive Models --
14 Feature Extraction By Mlp --
15 Final System Overview --
16 Conclusions --
Acronyms.
Series Title: Springer International Series in Engineering and Computer Science, VLSI, Computer Architecture and Digital Signal Processing, 247.
Responsibility: by Hervé A. Bourlard, Nelson Morgan.

Abstract:

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  Read more...

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