虚拟导航交互式Agent的语音到文本处理

Dian Ahkam Sani, Muchammad Saifulloh
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引用次数: 2

摘要

科技的发展是用计算机取代人类交互方式的一种方式,其中之一就是提供语音输入。用反向传播方法将声音转换为文本形式可以通过特征提取来理解和实现,其中包括使用线性预测编码(LPC)。线性预测编码是一种表示信号的方法,可以获得每个声音模式的特征。简而言之,这种语音识别系统的工作方式是通过麦克风输入人的声音(模拟信号),然后以8000hz的采样速度在计算机上的声卡的帮助下将其变成数字信号。然后,利用LPC将来自样品的数字信号进入初始过程,从而获得多个LPC系数。然后使用反向传播学习方法训练LPC输出。学习的结果用一个词分类,然后存储在数据库中。测试结果以能够显示语音情节的介绍程序的形式出现。在Real Time测试的100个数据中,语音识别结果与数据库中应答者的语音识别百分比为80%
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Speech to Text Processing for Interactive Agent of Virtual Tour Navigation
The development of science and technology is one way to replace the method of human interaction with computers, one of which is to provide voice input. Conversion of sound into text form with the Backpropagation method can be understood and realized through feature extraction, including the use of Linear Predictive Coding (LPC). Linear Predictive Coding is one way to represent the signal in obtaining the features of each sound pattern. In brief, the way this speech recognition system worked was by inputting human voice through a microphone (analog signal) which then sampled with a sampling speed of 8000 Hz so that it became a digital signal with the assistance of sound card on the computer. The digital signal from the sample then entered the initial process using LPC, so that several LPC coefficients were obtained. The LPC outputs were then trained using the Backpropagation learning method. The results of the learning were classified with a word and stored in a database afterwards. The results of the test were in the form of an introduction program that able display the voice plots. the results of speech recognition with voice recognition percentage of respondents in the database iss 80% of the 100 data in the test in Real Time
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