Spoken Language Understanding Software for Language Learning

نویسندگان

  • Hassan Alam
  • Aman Kumar
  • Fuad Rahman
  • Rachmat Hartono
  • Yuliya Tarnikova
چکیده

In this paper we describe a preliminary, work-in-progress Spoken Language Understanding Software (SLUS) with tailored feedback options, which uses interactive spoken language interface to teach Iraqi Arabic and culture to second language learners. The SLUS analyzes input speech by the second language learner and grades for correct pronunciation in terms of supra-segmental and rudimentary segmental errors such as missing consonants. We evaluated this software on training data with the help of two native speakers, and found that the software recorded an accuracy of around 70% in law and order domain. For future work, we plan to develop similar systems for multiple languages.

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تاریخ انتشار 2013