Development of the Oral Examination Assessment System (SIPENILAI) in Japanese Using Latent Semantic Analysis (LSA) Algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

SIPENILAI is an automatic oral exam and grading system that has been developed by the Electrical Engineering Department Universitas Indonesia. The system developed in this thesis uses the google speech recognition API and LSA methods for assessment. The Google speech recognition API processes voice input which is then converted as text. LSA method looks for similarities between two documents and the Frobenius norm for assessment scores. Based on testing that has been done the average value of SIPENILAI accuracy is 83.64% for fluent users and 76.89% for non-fluent users.

Original languageEnglish
Title of host publicationICCIP 2020 - 2020 6th International Conference on Communication and Information Processing
PublisherAssociation for Computing Machinery
Pages12-19
Number of pages8
ISBN (Electronic)9781450388092
DOIs
Publication statusPublished - 27 Nov 2020
Event6th International Conference on Communication and Information Processing, ICCIP 2020 - Virtual, Online, Japan
Duration: 27 Nov 202029 Nov 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference6th International Conference on Communication and Information Processing, ICCIP 2020
Country/TerritoryJapan
CityVirtual, Online
Period27/11/2029/11/20

Keywords

  • Frobenius Norm
  • Google speech recognition API
  • Latent Semantic Analysis
  • SIPENILAI

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