| 期刊全稱(chēng) | Blind Speech Separation | | 影響因子2023 | Shoji Makino,Hiroshi Sawada,Te-Won Lee | | 視頻video | http://file.papertrans.cn/190/189152/189152.mp4 | | 發(fā)行地址 | cutting edge topic on blind source separation.top researchers from all over the world.tutorial in nature and in-depth treatment | | 學(xué)科分類(lèi) | Signals and Communication Technology | | 圖書(shū)封面 |  | | 影響因子 | We are surrounded by sounds. Such a noisy environment makes it di?cult to obtain desired speech and it is di?cult to converse comfortably there. This makes it important to be able to separate and extract a target speech signal from noisy observations for both man–machine and human–human communication. Blindsourceseparation(BSS)isanapproachforestimatingsourcesignals using only information about their mixtures observed in each input channel. The estimation is performed without possessing information on each source, such as its frequency characteristics and location, or on how the sources are mixed. The use of BSS in the development of comfortable acoustic com- nication channels between humans and machines is widely accepted. Some books have been published on BSS, independent component ana- sis (ICA), and related subjects. There, ICA-based BSS has been well studied in the statistics and information theory ?elds, for applications to a variety of disciplines including wireless communication and biomedicine. However, as speech and audio signal mixtures in a real reverberant environment are generally convolutive mixtures, they involve a structurally much more ch- lenging task than instant | | Pindex | Book 2007 |
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