Article  |   January 2012
Measuring Speech-Sound Learning Using Visual Analog Scaling
Author Affiliations
  • Benjamin Munson
    Department of Speech-Language-Hearing Sciences, University of Minnesota, Twin Cities, MN
  • Sarah K. Schellinger
    Department of Speech-Language-Hearing Sciences, University of Minnesota, Twin Cities, MN
  • Kari Urberg Carlson
    Department of Speech-Language-Hearing Sciences, University of Minnesota, Twin Cities, MN
Article Information
Development / Attention, Memory & Executive Functions / Speech, Voice & Prosody
Article   |   January 2012
Measuring Speech-Sound Learning Using Visual Analog Scaling
SIG 1 Perspectives on Language Learning and Education, January 2012, Vol. 19, 19-30. doi:10.1044/lle19.1.19
SIG 1 Perspectives on Language Learning and Education, January 2012, Vol. 19, 19-30. doi:10.1044/lle19.1.19

The ultimate goal for speech-language pathologists is to align the linguistic behaviors of the clients whom we serve with those of the ambient language of the community. In light of this goal, it is critical that change in speech production is measured accurately. In this article, we review the use of visual analog scaling as a measure of change in children’s speech production. Following a discussion of this tool, the authors consider the clinical utility of this type of measurement.

Acknowledgments
The stimuli used in the studies described in this article were supported by NIH grant DC02932 to Jan Edwards. The research developing VAS for the assessment of children’s speech was supported by NSF grant BCS 0729277 to Benjamin Munson. That grant was part of the larger project using machine learning to model the interplay of production dynamics and perception dynamics in phonological acquisition. I thank the other principal investigators on that grant, Jan Edwards and Mary E. Beckman, for their important input in this endeavor. I gratefully acknowledge Fangfang Li for her work analyzing the acoustic characteristics of the fricatives used in the experiments described in this study and Eunjong Kong for her work analyzing the stop consonants.
Become a SIG Affiliate
Pay Per View
Entire SIG 1 Perspectives on Language Learning and Education content & archive
24-hour access
This Issue
24-hour access
This Article
24-hour access