Dynamic Estimation of Phoneme Confusion Patterns with a Genetic Algorithm to Improve the Performance of Metamodels for Recognition of Disordered Speech

2013 ◽  
pp. 175-187
Author(s):  
Santiago Omar Caballero-Morales ◽  
Felipe Trujillo-Romero
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Estimation ◽  
Disordered Speech

“I Can See What You’re Saying”: Clinical Utility of Spectral Moment Analysis

2011 ◽  
Vol 21 (2) ◽  
pp. 44-54
Author(s):  
Kerry Callahan Mandulak
Keyword(s):  
Speech Production ◽  
Speech Signal ◽  
Clinical Utility ◽  
Acoustic Analysis ◽  
Moment Analysis ◽  
Analysis Tool ◽  
Spectral Moment ◽  
Clinical Measure ◽  
Perceptual Analysis ◽  
Disordered Speech

Spectral moment analysis (SMA) is an acoustic analysis tool that shows promise for enhancing our understanding of normal and disordered speech production. It can augment auditory-perceptual analysis used to investigate differences across speakers and groups and can provide unique information regarding specific aspects of the speech signal. The purpose of this paper is to illustrate the utility of SMA as a clinical measure for both clinical speech production assessment and research applications documenting speech outcome measurements. Although acoustic analysis has become more readily available and accessible, clinicians need training with, and exposure to, acoustic analysis methods in order to integrate them into traditional methods used to assess speech production.

Physiologic Studies Provide New Perspectives on Early Speech Development

2010 ◽  
Vol 20 (2) ◽  
pp. 29-36
Author(s):  
Erin M. Wilson ◽  
Ignatius S. B. Nip
Keyword(s):  
Motor Control ◽  
Motor Development ◽  
Motion Tracking ◽  
Speech Development ◽  
Speech Motor Control ◽  
Therapeutic Approaches ◽  
Facial Motion ◽  
Disordered Speech ◽  
Speech Motor ◽  
Physiologic Data

Abstract Although certain speech development milestones are readily observable, the developmental course of speech motor control is largely unknown. However, recent advances in facial motion tracking systems have been used to investigate articulator movements in children and the findings from these studies are being used to further our understanding of the physiologic basis of typical and disordered speech development. Physiologic work has revealed that the emergence of speech is highly dependent on the lack of flexibility in the early oromotor system. It also has been determined that the progression of speech motor development is non-linear, a finding that has motivated researchers to investigate how variables such as oromotor control, cognition, and linguistic factors affect speech development in the form of catalysts and constraints. Physiologic data are also being used to determine if non-speech oromotor behaviors play a role in the development of speech. This improved understanding of the physiology underlying speech, as well as the factors influencing its progression, helps inform our understanding of speech motor control in children with disordered speech and provide a framework for theory-driven therapeutic approaches to treatment.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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