Exploring Content Features for Automated Speech Scoring

  title={Exploring Content Features for Automated Speech Scoring},
  author={Shasha Xie and Keelan Evanini and Klaus Zechner},
Most previous research on automated speech scoring has focused on restricted, predictable speech. For automated scoring of unrestricted spontaneous speech, speech proficiency has been evaluated primarily on aspects of pronunciation, fluency, vocabulary and language usage but not on aspects of content and topicality. In this paper, we explore features representing the accuracy of the content of a spoken response. Content features are generated using three similarity measures, including a lexical… CONTINUE READING
Highly Cited
This paper has 59 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 32 extracted citations

60 Citations

Citations per Year
Semantic Scholar estimates that this publication has 60 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 21 references

Validating automated speaking tests

  • Jared Bernstein, Alistair Van Moere, Jian Cheng.
  • Language Testing, 27(3):355–377.
  • 2010
3 Excerpts

Spoken language technology for education

  • Maxine Eskenazi, Abeer Alwan, Helmer Strik.
  • Speech Communication, 51(10):831–1038.
  • 2009
1 Excerpt

A constructdriven approach to score spontaneous non - native speech

  • TM Speechrater
  • 2007