基于流形学习与特征融合的汉语方言辨识

提出了一种基于流形学习的特征提取方法，将流形学习有效地应用于汉语方言辨识。针对语音语谱特征空间维数较高的问题，利用局部线性嵌入（LLE）方法降维并与MFCC特征进行融合，融合结果作为新特征用于汉语方言辨识。仿真实验表明，LLE算法能够获取汉语方言的本征规律，融合后的特征能够有效地提高汉语方言辨识的正确识别率。

Chinese dialect identification based on manifold learning and feature fusion

A feature extraction method based on manifold learning is proposed. Focusing on the high dimension among the spectrogram feature spaces, the locally linear embedding algorithm is applied to dimension reduction, and the feature is fused with Mel Frequency Cepstrum Coefficient（MFCC）, and the fusion result is used as a new feature in Chinese dialect identification system. The manifold learning method is effectively applied to Chinese dialect identification system. Simulation results show that the Locally Linear Embedding（LLE） algorithm can obtain the intrinsic law of dialects, and the fused characteristics can effectively improve the correct recognition rate of Chinese dialect identification.