rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Connectionist Speech Recognition
    sub title: a Hybrid Approach
  name:
    name part: Bourlard, Hervé A.
    role:
      role term: creator
  name:
    name part: Morgan, Nelson.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: mau
    date issued: 1994
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (xxix, 313 pages)
  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 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.
  note: by Hervé A. Bourlard, Nelson Morgan.
  note: Electronic resource.
  subject:
    topic: Engineering
  subject:
    topic: Computer engineering
  subject:
    topic: Systems engineering
  subject:
    topic: Computer engineering
  subject:
    topic: Engineering
  subject:
    topic: Systems engineering
  classification: TK7888.4
  classification: 621.3815
  related item:
    title info:
      title: Springer International Series in Engineering and Computer Science, VLSI, Computer Architecture and Digital Signal Processing ; 247
  identifier: 9781461532101 (electronic bk.)
  identifier: 1461532108 (electronic bk.)
  identifier: 9781461364092
  identifier: 1461364094
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: AU@
    record creation date: 121227
    record change date: 20260422222149.3
    record identifier: in00003575055
    language of cataloging:
      language term: eng