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Automatic Evaluation of Children's Performance on an English Syllable Blending Task
 

Summary: Automatic Evaluation of Children's Performance
on an English Syllable Blending Task
This work was supported in part by NSF Grant No. 0326214 and by a fellowship from the Radcliffe Institute for advanced study to Abeer Alwan.
Shizhen Wang1
, Patti Price2
, Margaret Heritage3
and Abeer Alwan1
1
Department of Electrical Engineering, University of California, Los Angeles
2
PPRICE Speech and Language Technology Consulting
3
National Center for Research on Evaluation, Standards, and Student Testing, UCLA
szwang@ee.ucla.edu, pjp@pprice.com, mheritag@ucla.edu and alwan@ee.ucla.edu
Abstract
In this paper, speech recognition techniques are applied to
automatically evaluate children's performance in a syllable
blending task. Word verification is performed to filter out
utterances pronounced incorrectly. For valid words, forced
alignment is applied to generate syllable segmentations and

  

Source: Alwan, Abeer - Electrical Engineering Department, University of California at Los Angeles

 

Collections: Computer Technologies and Information Sciences