Spoken Language Understanding Software for Language Learning
Hassan Alam, Aman Kumar, Fuad Rahman, Rachmat Hartono, Yuliya Tarnikova
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. Full Text
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