Research on Speaker Aware Training Method Based on Improved i-vector

The performance of speaker aware training method based on i-vector is poor because of using MFCC which has the relative poor robustness as the input feature for the extraction of the i-vector.To solve this problem,an improved i-vector based speaker aware training method is proposed.Firstly,a low dimensional feature extraction method based on SVD is proposed,and then the feature extracted by this method is used to replace the MFCC,which can extract better i-vector.Experimental results show that,in the Vystadial_cz corpus,compared with the DNN-HMM speech recognition system and the original i-vector based speaker aware training method,the recognition performance of this method is increased by 1.62% and 1.52% respectively,in the WSJ corpus,the recognition performance of this method is increased by 3.9% and 1.48% respectively.

# Computer engineering. Computer hardware # Computer software # speaker aware training|i-vector|deep neural network(dnn)|singular value matrix decomposition(svmd)|bottleneck feature

LIANG Yulong,QU Dan,QIU Zeyu (2018). "Research on Speaker Aware Training Method Based on Improved i-vector". Jisuanji gongcheng. https://doi.org/10.19678/j.issn.1000-3428.0046946