首页> 外文会议>MEC International Conference on Big Data and Smart City >Smart Solution to manage computer files and compose text documents using Hidden Markov Model’s Algorithm and Code Excited Linear Prediction Algorithm for Physically Challenged User
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Smart Solution to manage computer files and compose text documents using Hidden Markov Model’s Algorithm and Code Excited Linear Prediction Algorithm for Physically Challenged User

机译:智能解决方案来管理计算机文件并使用隐藏的Markov模型的算法编写文本文档和用于物理挑战用户的代码激励线性预测算法

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The proposed research is to study the relevance on speech recognition and synthesis to solve the challenges faced by physically disabled in the context of digital legacy and to cater to the smart city concept even to the physically challenged. In order to support the research thorough literature on speech recognition and synthesis is conducted and Hidden Markov Model's Algorithm and Code Excited Linear Prediction Algorithm were chosen to be the most effective technique towards finding an amicable solution to the problems faced by the physically challenged in terms of using a desktop and portable devices which uses Microsoft operating systems. The algorithm would be implemented by exploiting the features of C# which enables Windows application for Microsoft Windows platform to be operated on user's speech command. Through developing this application, it would create an affordable interactive system to assist the user in managing many of the Windows operated computer functions through speech recognizing the queries and commands from the user as input and responding back with the appropriate commanded functions as output with apt feedback to the user. The expected stakeholders/users of this application particularly could be any user who faces difficulty in typing causing repetitive strain injury, users with any kind of physical disabilities still could vocally communicate, users facing dyslexia and anyone who is interested to handle desktop hands free.
机译:该拟议的研究是研究语音识别和综合的相关性,以解决在数字遗产的背景下的身体残疾,甚至迎合身体挑战的智能城市概念所面临的挑战。为了支持研究语音识别和合成的彻底文献,并进行了隐藏的Markov模型的算法和代码激发线性预测算法是选择最有效的方法,以便在物理挑战所面临的问题上找到友好的解决方案使用使用Microsoft操作系统的桌面和便携式设备。该算法将通过利用C#的功能来实现,这使得Windows应用程序能够在用户的语音命令上运行Microsoft Windows平台。通过开发此应用程序,它将创建一个经济实惠的交互式系统,以帮助用户通过语音识别来自用户的查询和命令作为输入的查询和命令来管理许多Windows操作的计算机功能,并使用适当的命令功能作为具有APT反馈的输出给用户。本申请的预期利益相关者/用户可能是任何面临难以打字造成重复应变伤害的用户,任何类型的身体残疾的用户仍然可以呼吸障碍,面临诵读障碍和有兴趣处理桌面的任何人的用户自由。

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