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PHONEMES CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK BASED ON SPEECH SPECTRUM FEATURES

机译:基于语音频谱特征的人工神经网络语音分类

摘要

A METHOD FOR CLASSIFY PHONEMES AND/OR SYLLABLES PRONOUNCED BY HEARING-IMPAIRED PEOPLE UTILIZING ARTIFICIAL NEURAL NETWORK BASED ON SPEECH SPECTRUM FEATURES. USER DETAILS OR INFORMATION ARE STORED PRIOR TO THE SYSTEM (1). PHONEMES AND/OR SYLLABLES ARE PRESENTING TO USER (2) AND THE PRONUNCIATION OR UTTERANCE IS RECORDED VIA AN AUDIO INPUT DEVICE (3). PERCEPTUAL LINEAR PREDICTION (PLP) IS APPLIED FOR ANALYZING THE PRONOUNCED TARGET SYLLABLES AND A SPEECH SPECTRUM IS PRODUCED (4). SPEECH SPECTRUM IS SEGMENTING TO LOCATE THE CONSONANT-TO-VOWEL (CV) TRANSITION BORDER AND TO REMOVE NON-SYLLABLE SIGNAL (5). SEGMENTED SPEECH SPECTRUM IS USING AS INPUT DATA FOR IDENTIFICATION BY THE MULTILAYER PERCEPTRON (MLP) NETWORK (6). ACCOMPANYING DRAWING: FIGURE 1
机译:一种基于语音频谱特征的听觉受损人利用人工神经网络对音素和/或音节进行分类的方法。用户详细信息或信息已存储在系统(1)之前。语音和/或音节正呈现给用户(2),并且通过音频输入设备(3)记录了发音或轻音。感知线性预测(PLP)用于分析预定的目标音节并生成语音频谱(4)。语音频谱正在分部以定位语音到语音(CV)的过渡边界,并删除非对称信号(5)。分段语音频谱用作输入数据,以通过多层感知器(MLP)网络进行识别(6)。随附图纸:图1

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