Research of Aircraft Engine Sound Recognition Method Based on GMM-UBM
毫鸽 杨 · Computer Science and Application · 2017
高斯混合模型–通用背景模型(Gaussian mixture model-universal background model, GMM-UBM)是说话人识别技术中最为常用的模型，该模型在诸多试验中都取得了很好的效果。本设计探索把GMM-UBM模型用在异常声音检测中，通过对飞机发动机声音信号的处理，提取梅尔频率倒谱(MFCC)特征参数，训练UBM模型，用MAP自适应的算法得到GMM-UBM模型，用GMM-UBM模型检测识别发动机声音。实验证明，该方法优化了由于外界干扰变化导致的识别率下降的问题。 Gaussian mixture model-universal background model (GMM-UBM) is the most commonly used model in speaker recognition technology; the model has achieved very good results in many ex-periments. In this design, the GMM-UBM model is used in the abnormal sound detection. First, we process the aircraft engine sound signal, second extract the MFCC characteristic parameters, then train UBM model and last obtain the GMM-UBM model by MAP adaptive algorithm. The ultimate goal of the test indicates that the method could optimize the recognition rate decline due to interference change.