关键词: 语音识别, 双微阵列, 卷积神经网络, 噪声环境, 稳健性

Abstract: In order to solve the low speech recognition rate in noise environment, and the difficulty of traditional beamforming algorithm in dealing with spatial noise problem, an improved Minimum Variance Distortionless Response (MVDR) beamforming method based on dual micro-array was proposed. Firstly, the gain of micro-array was increased by diagonal loading, and the computational complexity was reduced by the inversion of recursive matrix. Then, through the modulation domain spectrum subtraction for further processing, the problem that music noise was easily produced by general spectral subtraction was solved, effectively reducing speech distortion, and well suppressing the noise. Finally, the Convolution Neural Network (CNN) was used to train the speech model and extract the deep features of speech, effectively solve the problem of speech signal diversity. The experimental results show that the proposed method achieves good recognition effect in the CNN trained speech recognition system, and has the speech recognition accuracy of 92.3% in F16 noise environment with 10 dB signal-to-noise ratio, means it has good robustness.

Key words: speech recognition, dual micro-array, Convolutional Neural Network (CNN), noise environment, robustness