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(PDF) Automatic Speech Recognition
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Added on 2019-12-28
(PDF) Automatic Speech Recognition
Added on 2019-12-28
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The usefulness of using AutomaticSpeech Recognition (ASR)Eyespeak software in improvingstudents English pronunciation
TABLE OF CONTENTABSTRACT.....................................................................................................................................3INTRODUCTION...........................................................................................................................31. Basic Concept of ASR............................................................................................................32. ASR in improvising student's English pronunciation.............................................................53. Dimensions of ASR based CALL...........................................................................................53.1 Pedagogical requirements.....................................................................................................63.1.1 Input...................................................................................................................................63.1.2 Output.................................................................................................................................63.1.3 Feedback............................................................................................................................63.2 Audio and visual sessions of training....................................................................................73.3 Speech technology in language learning...............................................................................74. Effectiveness of ASR..............................................................................................................75. ASR for teaching pronunciation..............................................................................................9CONCLUSION..............................................................................................................................10REFERENCES..............................................................................................................................11
ABSTRACTIt is basically in context to the present carried study that has entirely focussed upondefining the reliable means of Automated Speech Recognition (ASR) technology in teachingEnglish pronunciation to scholars. It is with a fundamental intercession of those learners forwhom English is referred to be a secondary language and are thus concerned about improving itspronunciation. The below survey has therefore evaluated different conceptual measures of ASRsoftware where it is hereby considered to be a leading supportive mean to help the scholars withits distinct set of tools that operates as per their configured styles of learning.INTRODUCTIONTechnical evolution is at a higher pace of development to operate in today's progressiveenvironment of work. However, it is together believed that there are still certain conceptualarenas in the current status of technological progression that is required to be acquire somegenuine self-reliant system. This can be done by inculcating the scheme of an alert yet artificialsystems of intelligence that communicates in a real way that predicts like humans. This ispresently stipulated to be a major concern of dealing with an obscure situation where thescientists are steadily progressing towards experimenting the same (Beelders and Blignaut,2011). It is thence considered to be a future context of continual developments that is prevailingat a higher pace of improvement. Automated Speech Recognition (ASR) technology depicts asimilar possession of technical development where it has showcased some authentic flow ofinvention that is beneficial for some specialised set of users. ASR is referred to be a leadingtechnical device that tends to allow the humans to utilise their vocalism to interact with a dataprocessor program which usually reflects a pivotal referral of computer interface. In this way, itis one of the most intelligent fluctuation that resembles a general form of conversation amonghuman beings.1. Basic Concept of ASRSpeech recognition (SR) has a greater importance in the field of electrical engineeringand computer science where it basically tends to translate the expressed words or content intotextual matter. It is yet another term that is used for ASR and is also known as speech to text(STT). ASR is a software that is autonomous in nature and is composed of computer drivenrecording to convert the explicit speech in decipherable textual matter (Demenko, 2009). In
context to which, ASR is basically interpreted to be a technical measure that permit theelectronic device to determine the phrases that is being spoken by an individual via telephonicdevice or microphone for converting it into textual content. It is referred to be a machine thatinterprets any sort of fluently verbalized speech that showcase 100% quality and accuracy inapprehension of all type of languages.However, there still exists certain state of dilemma where it is unable to comprehend insuch audible surrounding in which an individual is not able to make a clear and fluent statement.Due to which, its regular usage is tending to enhance on daily basis with lot more inculcation ofdistinct applications (Cucchiarini, 2009). With an analogous reference to which, ASR with aneventual intent of getting into a more broader form of investigation is attempting to allow theconfigured systems to improvise their recognition power with much larger set of vocabularies. Itis mainly in context to apply this aided tool of ASR in learning second level languages with amajor intercession of international languages with an ease of intercepting its distinct set ofpronunciation.ASR is hence used as an Eyespeak software for improvising the English pronunciation offoreign students. It is especially for the students who are trying to assimilate the English as asecondary language often tends to showcase a prior tendency of improvising their pronunciationwhere they can aptly communicate with the help of it (Kim, 2006). There exists a mostprogressive interpretation of currently developed ASR technologies that is known as NaturalLanguage Processing (NLP). It is one of the most advanced variant of ASR that is nearest toallow the individuals to make a real conversation with the intellectual set of machine where it isalso referred to have some more possibility of enhancement. It is basically due to its reluctantstate of quality where it gives only 96 to 99% of accuracy.This is for instance to specify some highly advanced systems of Siri interface in iPhonethat tends to aid the individuals in making an open ended chat that imitates a real conversation. Itthereby gives lot more choices to the humans referring to the same instead of showcasing limitedset of words (Demenko, Wagner and Cylwik, 2010). Directed dialogue conversation is yetanother simplex form of ASR where it is with a limited assistance of choices that can be chosenby the human to converse with the machine interface. In context to which, it tends to offernarrowly outlined requests to the individuals for acquiring considerable knowledge that is out ofthe contented arena. This is for instance to illustrate about some substantial means of machine-
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