高校物业管理国外论文发表

The necessity for accurate speech recognition systems capableof handling adverse environments with multiple speakershas in recent years fueled speech separation and enhancementresearch [1, 5, 3, 2, 6, 4]. This has resulted in numeroustechniques with varying degrees of success, most ofwhich employ multiple microphones [1, 3, 2, 6, 4]. Beamformingtechniques, for example, utilize knowledge aboutthe direction of the speech source of interest in order to reducenoise from other directions. The resulting SNR gainis significant as long as a large number of microphones areavailable [6, 4]. Independent Component Analysis (ICA),on the other hand, is capable of producing large SNR gainswith few microphones [1, 3]. However, ICA has severallimitations that have hampered its application in real-worldsituations [1, 6].Interestingly, both of these popular techniques (as wellas many other speech separation techniques) are similar inthe sense that they are not specifically designed to functionfor speech signals. Speech has certain characteristics whoseutilization can provide a significant edge in the de-noisingand signal separation tasks [2, 5].In this paper, we extend the phase error filtering techniqueinitially proposed in [2] to include the magnitudesof the two microphones in addition to the phase information.This technique transforms two noisy time-domain signalsrecorded by two microphones into their time-frequency(TF) representations. For each time-frequency componentor block, a phase-error measure is derived from the informationin both microphones. Based on this, the time-frequencyblock for each microphone is scaled by a masking value betweenzero and one. Basically, TF blocks with large phaseerrorsare ‘punished’ by a small mask value (0) and TFblocks with small phase-errors are ‘rewarded’ by a largemask value (1).In the following sections, we formulate four different TFmasks and analyze them theoretically, through SNR-gainsimulations, and digit recognition experiments.

国外比较专业的论文发表在SCI。

SCI 期刊中文名是《科学引文索引》，是美国科学情报研究所出版的一个期刊文献检索工具。因其严格的选刊标准和评估程序，以及其收录的论文能够全面覆盖全世界多数重要和有影响力的研究成果。而成为了国内大部分科研机构、高校等单位考核评价标准。

《英语广场》省级知网首页可查，SCD期刊，目前正常收21年2-3月的刊期，另外有个别年内版面可以免费加急到年底出刊，注意他的版面是按字算，不是字符。《现代英语》万方收录的期刊，只收英语高教的文章。如果是文学的，如果必须是年内的。

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以上内容参考：百度百科--论文