基于音高检测的同信道语音相位空间状态分类方法

Haiyan Guo, Xi Shao, Zhen Yang
{"title":"基于音高检测的同信道语音相位空间状态分类方法","authors":"Haiyan Guo, Xi Shao, Zhen Yang","doi":"10.1109/ICOSP.2008.4697222","DOIUrl":null,"url":null,"abstract":"This paper presents an improved phase-space voicing state classification method based on pitch detection to simultaneously determine the voicing state of two speakers present in a segment of co-channel speech. Three possible voicing states are considered: Unvoiced/Unvoiced (U/U), Voice/Unvoiced (V/U), Voiced/Voiced (V/V). Firstly, the method employs a phase-space voicing-state classification algorithm to classify co-channel speech into three parts: U/U frames, V/U frames and V/V frames. Secondly, in order to decrease misjudgment between V/U and V/V frames, we introduce mulitpitch detection based on enhanced summary autocorrelation function (ESACF) to modify the voicing states of V/V frames and single pitch detection based on autocorrelation function (ACF) to modify the voicing states of V/U frames. Experiments show the proposed method effectively reduces the classification error rate and outperforms the voicing-state classification algorithm only based on phase-space reconstruction.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"1164 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An improved phase-space voicing-state classification for co-channel speech based on pitch detection\",\"authors\":\"Haiyan Guo, Xi Shao, Zhen Yang\",\"doi\":\"10.1109/ICOSP.2008.4697222\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an improved phase-space voicing state classification method based on pitch detection to simultaneously determine the voicing state of two speakers present in a segment of co-channel speech. Three possible voicing states are considered: Unvoiced/Unvoiced (U/U), Voice/Unvoiced (V/U), Voiced/Voiced (V/V). Firstly, the method employs a phase-space voicing-state classification algorithm to classify co-channel speech into three parts: U/U frames, V/U frames and V/V frames. Secondly, in order to decrease misjudgment between V/U and V/V frames, we introduce mulitpitch detection based on enhanced summary autocorrelation function (ESACF) to modify the voicing states of V/V frames and single pitch detection based on autocorrelation function (ACF) to modify the voicing states of V/U frames. Experiments show the proposed method effectively reduces the classification error rate and outperforms the voicing-state classification algorithm only based on phase-space reconstruction.\",\"PeriodicalId\":445699,\"journal\":{\"name\":\"2008 9th International Conference on Signal Processing\",\"volume\":\"1164 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 9th International Conference on Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.2008.4697222\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 9th International Conference on Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2008.4697222","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了一种改进的基于基音检测的相空间语音状态分类方法,用于同时确定同信道语音段中两个说话人的语音状态。考虑三种可能的发声状态:未发声/未发声(U/U),发声/未发声(V/U),发声/发声(V/V)。该方法首先采用相空间语音状态分类算法,将同信道语音分为U/U帧、V/U帧和V/V帧三部分。其次,为了减少V/U和V/V帧之间的误判,引入基于增强摘要自相关函数的多基音检测(ESACF)来修改V/V帧的发声状态,引入基于自相关函数的单基音检测(ACF)来修改V/U帧的发声状态。实验表明,该方法有效地降低了分类错误率,优于仅基于相空间重构的语音状态分类算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An improved phase-space voicing-state classification for co-channel speech based on pitch detection
This paper presents an improved phase-space voicing state classification method based on pitch detection to simultaneously determine the voicing state of two speakers present in a segment of co-channel speech. Three possible voicing states are considered: Unvoiced/Unvoiced (U/U), Voice/Unvoiced (V/U), Voiced/Voiced (V/V). Firstly, the method employs a phase-space voicing-state classification algorithm to classify co-channel speech into three parts: U/U frames, V/U frames and V/V frames. Secondly, in order to decrease misjudgment between V/U and V/V frames, we introduce mulitpitch detection based on enhanced summary autocorrelation function (ESACF) to modify the voicing states of V/V frames and single pitch detection based on autocorrelation function (ACF) to modify the voicing states of V/U frames. Experiments show the proposed method effectively reduces the classification error rate and outperforms the voicing-state classification algorithm only based on phase-space reconstruction.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A novel pulse shaping method for Ultra-Wideband communications Matching pursuits with undercomplete dictionary A novel decision-directed channel estimator for OFDM systems Task analysis methods for data selection in task adaptation on mandarin isolated word recognition Combining LBP and Adaboost for facial expression recognition
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1