【摘要】 提出一种基于宽窄带语谱图融合分带投影的方法对特定人二字汉语词汇进行识别。该方法将图像处理技术应用到语音识别领域,在图像特征提取过程中,首先对窄带语谱图进行等宽度分带行投影和二进宽度分带行投影,并将其分别作为窄带语谱图的第1个特征集合和第2个特征集合,同时将窄带语谱图进行再次图像傅里叶变换之后进行等宽度行投影,作为第3个特征集合。然后对宽带语谱图进行等宽度分带列投影,作为第4个特征集合。将上述特征集合作为识别的特征向量,以支持向量机为分类器进行特定人二字汉语词汇整体识别。采用1000个语音样本进行仿真实验,结果表明,采用前3个特征集合的特征向量对特定人二字汉语词汇识别的正确识别率可达92.4%,采用第4个特征集合的特征值对特定人二字词汇识别的正确识别率可达80%,而采用上述4个特征集合的特征值融合对特定人二字汉语词汇识别的正确识别率可达95.4%。该特征融合的方法为汉语词汇的识别提供了新的思路。更多还原

【Abstract】 A method based on broadband and narrowband spectrogram fusion with zoning projection of specific two words Chinese lexical recognition was presented.In the process of image feature extraction,the image processing technique is applied to the speech recognition field.Firstly,equal width zoning line projection and binary width zoning line projection are carried out to the narrowband spectrogram,and they are set respectively as the narrowband spectrogram of the first characteristic set and the second characteristic set.Meanwhile,equal width zoning line projection is carried out again to the narrowband spectrogram after Fourier transform,treating it as the third feature set.Then,equal width column projection is carried out to the broadband spectrogram,regarding it as the fourth feature set.The above three feature sets are used as feature vectors to support vector machine(SVM)as a classifier for the overall recognition of specific two words Chinese vocabulary.1000 voice samples are used in simulation experiment.The results show that the correct recognition rate of the two words Chinese word recognition by the first three feature sets is 92.4%.The correct recognition rate of two words vocabulary recognition using fourth feature sets is 80%.The correct recognition rate of the two words Chinese word recognition by using the feature value fusion of the above four features can reach 95.4%.This method of feature fusion provides a new way of thinking of Chinese vocabulary overall recognition.更多还原