What Are The Advantages And Disadvantages Of Computer Assisted Language Learning

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Introduction
Since the last few decades, exercising the skills of spoken language has been receiving high degree of attention amongst the educators. The curricula of foreign language creates the main focus on the skills of productivity by laying special emphasis over the competence of communication. Since recent times, there have been advancements within the multimedia technology that has resulted in the emergence of computer assisted language learning as a tempting option towards traditional sources in order to supplement or replace direct interaction amongst the student and the teacher. This includes the study of language at the laboratory or the self-study on the basis of audio tape (Cervatiuc, 2007).
Technologies
Enabling the integration
Amongst all of these, there is a lack of framework of theory that is unified in order to design and evaluate the systems of computer assisted language learning (Diller, 2008). There is also lack of empirical evidence within the conclusion for the pedagogical advantages related to computers within the learning of language have contributed in raising both, demands as well as expectation imposed on the computer in the form of a potential tool of learning. In addition to this, finally, there are certain disadvantages and drawbacks within the technology itself. The rapid advancements in the technology for the years of 1980s have contributed in raising both, demands as well as expectation imposed on the computer in the form of a potential tool of learning. The researchers on acquisition of second language and educators have now been showing high level of demands for intelligence, systems of computer assisted language learning that are adaptive for the users that contribute in offering not only the tools of diagnosis that are highly sophisticated, but also provide effective mechanisms on feedback in order to create a focus on the learner with respect to areas that require the practices of
The recognition of speech automatically contributes in stringing together all of the relevant models for the formation of words (Diller, 2008). Recognition of the incoming signal of speech involves a match amongst the observed sequence that is acoustic along with a different set for the models of HMM. The model of HMM can contribute in modelling phones or other units with respect to sub word. In addition to this, it can become capable enough of modelling words or also the entire

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