Paper Title
Language Learning With Speech Recognition

Speech recognition system employed in language learning is a coherence of speech detection and analysis. This particular application of speech recognition where a person is put to test has a greater accuracy to other systems where the machine is put to test such as speech to text conversion, speech to command conversion etc. The advantage of language learning with speech recognition is that the system needs to do nothing more than its nomenclature. Then the question that arises at such a claim is that then what about error detection and diagnosis. The interesting fact is that any simple speech recognition system does error detection but rather struggles with itself to find the word that is pronounced but in language learning since a predefined word is to be analysed for pronunciation errors, the complexity of word identification is reduced to a greater extent. In this paper, we examine various studies and reviews on the usability of Automatic Speech Recognition (ASR) technology as a tool to train pronunciation in the second language. We show that part of the criticism that has been addressed to this technology is not warranted, being rather the result of limited familiarity with ASR technology and with broader Computer Assisted Language Learning (CALL) courseware design matters. In our analysis we also consider actual problems of state-of-the-art ASR technology, with a view to indicating how ASR can be employed to develop courseware that is both pedagogically sound and reliable.