6,058 research outputs found
ITS for Teaching French
Abstract: The paper depicts the blueprint of an electronic wise indicating system for demonstrating learning French to understudies to overcome the inconveniences they go up against. The fundamental idea of this structure is a proficient introduction into learning French. The system shows the purpose of learning French and coordinates thusly made issues for the understudies to clarify. The system is logically balanced at run time to the understudy’s individual progress. The system gives unequivocal help to adaptable presentation to learners
ITS for Teaching TOEFL
Abstract: An e-learning system is increasingly gaining popularity in the academic community because of several benefits of learning anywhere anyplace and anytime. An Intelligent Tutoring System (ITS) is a computer system that aims to provide immediate and customized instruction or feedback to learners, usually without requiring intervention from a human teacher.(ITSB) is the tutoring system Builder Which designed and improved to help teachers in building intelligent tutoring system in many fields .In this paper we have an example and an evaluating are presented of building an intelligent tutoring system for teaching TOEFL using ITSB tool
An Intelligent Tutoring System for Learning TOEFL
An e-learning system is increasingly gaining popularity in the academic community because of several benefits of learning anywhere anyplace and anytime. An Intelligent Tutoring System (ITS) is a computer system that aims to provide immediate and customized instruction or feedback to learners, usually without requiring intervention from a human teacher.(ITSB) is the tutoring system Builder Which designed and improved to help teachers in building intelligent tutoring system in many fields. In this paper, we have an example and an evaluating are presented of building an intelligent tutoring system for teaching TOEFL using ITSB tool
DDSupport: Language Learning Support System that Displays Differences and Distances from Model Speech
When beginners learn to speak a non-native language, it is difficult for them
to judge for themselves whether they are speaking well. Therefore,
computer-assisted pronunciation training systems are used to detect learner
mispronunciations. These systems typically compare the user's speech with that
of a specific native speaker as a model in units of rhythm, phonemes, or words
and calculate the differences. However, they require extensive speech data with
detailed annotations or can only compare with one specific native speaker. To
overcome these problems, we propose a new language learning support system that
calculates speech scores and detects mispronunciations by beginners based on a
small amount of unannotated speech data without comparison to a specific
person. The proposed system uses deep learning--based speech processing to
display the pronunciation score of the learner's speech and the
difference/distance between the learner's and a group of models' pronunciation
in an intuitively visual manner. Learners can gradually improve their
pronunciation by eliminating differences and shortening the distance from the
model until they become sufficiently proficient. Furthermore, since the
pronunciation score and difference/distance are not calculated compared to
specific sentences of a particular model, users are free to study the sentences
they wish to study. We also built an application to help non-native speakers
learn English and confirmed that it can improve users' speech intelligibility
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