Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders
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Beschreibung
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.
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.
Explores different approaches to evaluation of speech disorders and the impact of recording and evaluation methodologies, as a guide to future research and development in this area Presents a survey showing the potential offered by different technologies and identifying the most promising approaches to the automatic monitoring of speech disorder Includes supplementary material: sn.pub/extras
Autor*in
Ladan Baghai-Ravary
Themen in »Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders«
Markov Model Neural Networks Non-stationary signal models Signal processing techniques Speaker characterization Speech disorder assessment Speech production Speech recognition