{"title":"基于ica的手机语音通信降噪","authors":"Zhipeng Zhang, M. Etoh","doi":"10.1109/ICCCN.2007.4317863","DOIUrl":null,"url":null,"abstract":"We propose a frequency-domain independent component analysis (ICA) with robust and computationally-light post processing method for background noise reduction in mobile phone speech communication. In our scenario, multi-source signal separation is not the target, but noise reduction is the primal one. This primal target characterizes our approach that promotes a new physical constraint, in other words, we place a restriction on the amplitude range of the transfer functions rather than assuming that the amplitudes are constant. When there are diffraction, obstacles and reflections in the real-world environment, it is better to assume that transfer function amplitude (derived from the distance to the mouth) varies within a certain range. Our two-microphone experiment shows that the ICA-based noise reduction significantly improves speech recognition performance especially in severe noise conditions.","PeriodicalId":388763,"journal":{"name":"2007 16th International Conference on Computer Communications and Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"ICA-based Noise Reduction for Mobile Phone Speech Communication\",\"authors\":\"Zhipeng Zhang, M. Etoh\",\"doi\":\"10.1109/ICCCN.2007.4317863\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a frequency-domain independent component analysis (ICA) with robust and computationally-light post processing method for background noise reduction in mobile phone speech communication. In our scenario, multi-source signal separation is not the target, but noise reduction is the primal one. This primal target characterizes our approach that promotes a new physical constraint, in other words, we place a restriction on the amplitude range of the transfer functions rather than assuming that the amplitudes are constant. When there are diffraction, obstacles and reflections in the real-world environment, it is better to assume that transfer function amplitude (derived from the distance to the mouth) varies within a certain range. Our two-microphone experiment shows that the ICA-based noise reduction significantly improves speech recognition performance especially in severe noise conditions.\",\"PeriodicalId\":388763,\"journal\":{\"name\":\"2007 16th International Conference on Computer Communications and Networks\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 16th International Conference on Computer Communications and Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCN.2007.4317863\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 16th International Conference on Computer Communications and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCN.2007.4317863","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ICA-based Noise Reduction for Mobile Phone Speech Communication
We propose a frequency-domain independent component analysis (ICA) with robust and computationally-light post processing method for background noise reduction in mobile phone speech communication. In our scenario, multi-source signal separation is not the target, but noise reduction is the primal one. This primal target characterizes our approach that promotes a new physical constraint, in other words, we place a restriction on the amplitude range of the transfer functions rather than assuming that the amplitudes are constant. When there are diffraction, obstacles and reflections in the real-world environment, it is better to assume that transfer function amplitude (derived from the distance to the mouth) varies within a certain range. Our two-microphone experiment shows that the ICA-based noise reduction significantly improves speech recognition performance especially in severe noise conditions.