关键词: 汉语数字识别, 流形学习, 局部线性嵌入算法, 动态时间规整

Abstract: Speech signal dimensions are higher when the signal is transformed to frequency domain, manifold learning algorithm can find a smooth low-dimensional manifold embedded in the high-dimensional data space. The manifold learning algorithm is proposed to reduce the dimensions in the high-dimensional data for Mandarin digit speech recognition. Low-dimensional manifold structure is extracted from the high-dimensional frequency data based on locally linear embedding of manifold learning algorithms. Then the resulting low-dimensional data is inputted into Dynamic Time Warping（DTW） to recognize. Simulation results demonstrate that the dimensions are lower using Local Linear Embedding（LLE） compared with MFCC, the recognition rate increases by 1.2% in Mandarin digit speech recognition, and the recognition speed gets improved effectively.

Key words: Mandarin digit recognition, manifold learning algorithm, Locally Linear Embedding（LLE）, Dynamic Time Warping（DTW）