摘要
在HTK平台上实现非特定人的岩帅佤语孤立词语音识别;运用小波去噪原理对原始语音去噪,来提高语音段的信噪比;对有声段预处理、提取MFCC特征参数,训练和建立了HMM模型库,最后进行识别,结果提高了孤立词语音信号的准确性。
This research is aimed at realizing the recognition of the isolated word speech of the Ai Shuai Wa language. The wavelet denoising principle is used to denoise the original speech,thus greatly improving the signal to noise ratio of the speech segment. The MFCC feature parameters are extracted from the preprocessing of the sound segment, and the MFCC feature parameters are extracted to train the HMM model, and then the model library is formed. Finally,the recognition is carried out. The experimental results improve the accuracy of isolated word speech signals.
出处
《保山学院学报》
2017年第5期72-74,79,共4页
JOURNAL OF BAOSHAN UNIVERSITY
基金
云南省教育厅科学研究基金项目(项目编号:2017YJS056)