{"title":"为什么某些音频信号的短时傅里叶变换系数具有不均匀的相位分布","authors":"Stephen D. Voran","doi":"arxiv-2409.08981","DOIUrl":null,"url":null,"abstract":"The short-time Fourier transform (STFT) represents a window of audio samples\nas a set of complex coefficients. These are advantageously viewed as magnitudes\nand phases and the overall distribution of phases is very often assumed to be\nuniform. We show that when audio signal STFT phase distributions are analyzed\nper-frequency or per-magnitude range, they can be far from uniform. That is,\nthe uniform phase distribution assumption obscures significant important\ndetails. We explain the significance of the nonuniform phase distributions and\nhow they might be exploited, derive their source, and explain why the choice of\nthe STFT window shape influences the nonuniformity of the resulting phase\ndistributions.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why some audio signal short-time Fourier transform coefficients have nonuniform phase distributions\",\"authors\":\"Stephen D. Voran\",\"doi\":\"arxiv-2409.08981\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The short-time Fourier transform (STFT) represents a window of audio samples\\nas a set of complex coefficients. These are advantageously viewed as magnitudes\\nand phases and the overall distribution of phases is very often assumed to be\\nuniform. We show that when audio signal STFT phase distributions are analyzed\\nper-frequency or per-magnitude range, they can be far from uniform. That is,\\nthe uniform phase distribution assumption obscures significant important\\ndetails. We explain the significance of the nonuniform phase distributions and\\nhow they might be exploited, derive their source, and explain why the choice of\\nthe STFT window shape influences the nonuniformity of the resulting phase\\ndistributions.\",\"PeriodicalId\":501034,\"journal\":{\"name\":\"arXiv - EE - Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - EE - Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.08981\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08981","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Why some audio signal short-time Fourier transform coefficients have nonuniform phase distributions
The short-time Fourier transform (STFT) represents a window of audio samples
as a set of complex coefficients. These are advantageously viewed as magnitudes
and phases and the overall distribution of phases is very often assumed to be
uniform. We show that when audio signal STFT phase distributions are analyzed
per-frequency or per-magnitude range, they can be far from uniform. That is,
the uniform phase distribution assumption obscures significant important
details. We explain the significance of the nonuniform phase distributions and
how they might be exploited, derive their source, and explain why the choice of
the STFT window shape influences the nonuniformity of the resulting phase
distributions.