CASIA OpenIR  > 模式识别国家重点实验室  > 机器人视觉
Two-Stage Multi-Target Joint Learning for Monaural Speech Separation
Shuai, Nie1; Shan, Liang1; Wei, Xue1; XueLiang, Zhang2; WenJu, Liu1; Like Dong3; Hong Yang3
2015
会议名称Annual Conference of the International Speech Communication Association (INTERSPEECH)
会议录名称Annual Conference of the International Speech Communication Association (INTERSPEECH)
页码1503-1507
会议日期2015
会议地点Dresden Germany
摘要Recently, supervised speech separation has been extensively
studied and shown considerable promise. Due to the temporal
continuity of speech, speech auditory features and separation
targets present prominent spectro-temporal structures
and strong correlations over the time-frequency (T-F) domain,
which can be exploited for speech separation. However, many
supervised speech separation methods independently model
each T-F unit with only one target and much ignore these useful
information. In this paper, we propose a two-stage multi-target
joint learning method to jointly model the related speech separation
targets at the frame level. Systematic experiments show
that the proposed approach consistently achieves better separation
and generalization performances in the low signal-to-noise
ratio(SNR) conditions.
关键词Speech Separation Multi-target Learning Computational Auditory Scene Analysis (Casa)
收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11024
专题模式识别国家重点实验室_机器人视觉
作者单位1.National Laboratory of Patten Recognition, Institute of Automation, Chinese Academy of Sciences
2.College of Computer Science, Inner Mongolia University
3.Electric Power Research Institute of ShanXi Electric Power Company, China State Grid Corp
推荐引用方式
GB/T 7714
Shuai, Nie,Shan, Liang,Wei, Xue,et al. Two-Stage Multi-Target Joint Learning for Monaural Speech Separation[C],2015:1503-1507.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
ShuaiNie2015.pdf(185KB)会议论文 开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Shuai, Nie]的文章
[Shan, Liang]的文章
[Wei, Xue]的文章
百度学术
百度学术中相似的文章
[Shuai, Nie]的文章
[Shan, Liang]的文章
[Wei, Xue]的文章
必应学术
必应学术中相似的文章
[Shuai, Nie]的文章
[Shan, Liang]的文章
[Wei, Xue]的文章
相关权益政策
暂无数据
收藏/分享
文件名: ShuaiNie2015.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。