{"title":"基于卡尔曼滤波的高语音质量噪声抑制","authors":"N. Tanabe, T. Furukawa, H. Matsue, S. Tsujii","doi":"10.1109/ISPACS.2006.364895","DOIUrl":null,"url":null,"abstract":"We propose a noise suppression algorithm based on Kaiman filter. The algorithm achieves a noise suppression with high speech quality under the condition of the AWGN (additive white Gaussian noise), from the canonical state space models with a state equation composed of the clean speech signal and an observation equation composed of the clean speech signal and AWGN. The special feature of the proposed algorithm is realization of high speech quality noise suppression utilizing only the Kalman filter, while the conventional algorithm utilizes the linear prediction algorithm and the Kalman filter. The simulation results show that the proposed method improved the noise suppression capability by about 5 dB than that of the conventional method","PeriodicalId":178644,"journal":{"name":"2006 International Symposium on Intelligent Signal Processing and Communications","volume":"67 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Noise Suppression with High Speech Quality Based on Kalman Filter\",\"authors\":\"N. Tanabe, T. Furukawa, H. Matsue, S. Tsujii\",\"doi\":\"10.1109/ISPACS.2006.364895\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a noise suppression algorithm based on Kaiman filter. The algorithm achieves a noise suppression with high speech quality under the condition of the AWGN (additive white Gaussian noise), from the canonical state space models with a state equation composed of the clean speech signal and an observation equation composed of the clean speech signal and AWGN. The special feature of the proposed algorithm is realization of high speech quality noise suppression utilizing only the Kalman filter, while the conventional algorithm utilizes the linear prediction algorithm and the Kalman filter. The simulation results show that the proposed method improved the noise suppression capability by about 5 dB than that of the conventional method\",\"PeriodicalId\":178644,\"journal\":{\"name\":\"2006 International Symposium on Intelligent Signal Processing and Communications\",\"volume\":\"67 5\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Symposium on Intelligent Signal Processing and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPACS.2006.364895\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Symposium on Intelligent Signal Processing and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPACS.2006.364895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
提出了一种基于Kaiman滤波的噪声抑制算法。该算法从由纯净语音信号组成的状态方程和由纯净语音信号和加性高斯白噪声组成的观测方程的正则状态空间模型出发,实现了在加性高斯白噪声条件下的高质量语音抑制。该算法的特点是仅利用卡尔曼滤波器实现高语音质量的噪声抑制,而传统算法则利用线性预测算法和卡尔曼滤波器。仿真结果表明,该方法的噪声抑制能力比传统方法提高了约5 dB
Noise Suppression with High Speech Quality Based on Kalman Filter
We propose a noise suppression algorithm based on Kaiman filter. The algorithm achieves a noise suppression with high speech quality under the condition of the AWGN (additive white Gaussian noise), from the canonical state space models with a state equation composed of the clean speech signal and an observation equation composed of the clean speech signal and AWGN. The special feature of the proposed algorithm is realization of high speech quality noise suppression utilizing only the Kalman filter, while the conventional algorithm utilizes the linear prediction algorithm and the Kalman filter. The simulation results show that the proposed method improved the noise suppression capability by about 5 dB than that of the conventional method