Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders

  • Ladan Baghai-Ravary
  • Steve W. Beet

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Also part of the SpringerBriefs in Speech Technology book sub series (BRIEFSSPEECHTECH)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Ladan Baghai-Ravary, Steve W. Beet
    Pages 1-6
  3. Ladan Baghai-Ravary, Steve W. Beet
    Pages 7-11
  4. Ladan Baghai-Ravary, Steve W. Beet
    Pages 13-19
  5. Ladan Baghai-Ravary, Steve W. Beet
    Pages 21-37
  6. Ladan Baghai-Ravary, Steve W. Beet
    Pages 39-52
  7. Ladan Baghai-Ravary, Steve W. Beet
    Pages 53-63
  8. Ladan Baghai-Ravary, Steve W. Beet
    Pages 65-70

About this book

Introduction

Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders provides a survey of methods designed to aid clinicians in the diagnosis and monitoring of speech disorders such as dysarthria and dyspraxia, with an emphasis on the signal processing techniques, statistical validity of the results presented in the literature, and the appropriateness of methods that do not require specialized equipment, rigorously controlled recording procedures or highly skilled personnel to interpret results.

Such techniques offer the promise of a simple and cost-effective, yet objective, assessment of a range of medical conditions, which would be of great value to clinicians. The ideal scenario would begin with the collection of examples of the clients’ speech, either over the phone or using portable recording devices operated by non-specialist nursing staff.

The recordings could then be analyzed initially to aid diagnosis of conditions, and subsequently to monitor the clients’ progress and response to treatment. The automation of this process would allow more frequent and regular assessments to be performed, as well as providing greater objectivity.

Keywords

Markov Model Neural Networks Non-stationary signal models Signal processing techniques Speaker characterization Speech disorder assessment Speech production Speech recognition

Authors and affiliations

  • Ladan Baghai-Ravary
    • 1
  • Steve W. Beet
    • 2
  1. 1., Phonetics LaboratoryUniversity of OxfordOxfordUnited Kingdom
  2. 2.Aculab plcMilton KeynesUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-4574-6
  • Copyright Information The Author(s) 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Engineering
  • Print ISBN 978-1-4614-4573-9
  • Online ISBN 978-1-4614-4574-6
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • About this book
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