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Artificial neural network based method for handwriting recognition to speech generation

机译:基于人工神经网络的语音识别方法

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In this paper a new and original framework for handwriting to speech devices is investigated. This framework is based on a pen-shaped optical mouse connected to a human-machine interaction. The selected approach is divided in four steps: characters acquisition, characters digitalization, characters recognition and speech generation. Characters acquisition uses a pen-shaped optical mouse connected to a USB port. Characters digitalization is based on the extraction of the coordinates of the pen positions during the drawing of the characters, which are then sent to the character recognition module. This module is based on a artificial neural network algorithm. The identified letters are then put together to build words and possible typesetting errors are corrected. These words are sent one after the other to the speech generator to be pronounced which allow disabled people to communicate easily. Compared to others approaches, the key points and advantage of the proposed framework are the robustness of the algorithm, the real-time interaction, the size and weight of the device (and the price).
机译:本文研究了一种用于手写语音设备的新的原始框架。该框架基于连接到人机交互的笔形光学鼠标。所选方法分为四个步骤:字符获取,字符数字化,字符识别和语音生成。字符采集使用连接到USB端口的笔形光学鼠标。字符数字化基于字符绘制过程中笔位置坐标的提取,然后将其发送到字符识别模块。该模块基于人工神经网络算法。然后将识别出的字母放在一起以构建单词,并纠正可能的排版错误。这些单词一个接一个地发送到语音生成器,以使残疾人易于沟通。与其他方法相比,所提出框架的关键点和优势在于算法的鲁棒性,实时交互,设备的尺寸和重量(以及价格)。

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