Neuro-fuzzy filtering techniques for automatic speech recognition enhancement

R. Poluzzi, L. Arnone, A. Savi, M. Brescianini
{"title":"Neuro-fuzzy filtering techniques for automatic speech recognition enhancement","authors":"R. Poluzzi, L. Arnone, A. Savi, M. Brescianini","doi":"10.1109/ISP.2003.1275848","DOIUrl":null,"url":null,"abstract":"In order to enhance the percentage of recognised words for ASR (automatic speech recognition) systems, an adaptive neuro-fuzzy filtering technique in the time domain is proposed. Architecture of neural networks is shown having the purpose of exploiting spatial information, with the advantage of little computational load with respect to other classical beamforming techniques. Several results are described for complex acoustic scenarios with VOX ASR system by DIBE (University of Genova).","PeriodicalId":285893,"journal":{"name":"IEEE International Symposium on Intelligent Signal Processing, 2003","volume":"45 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Symposium on Intelligent Signal Processing, 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISP.2003.1275848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In order to enhance the percentage of recognised words for ASR (automatic speech recognition) systems, an adaptive neuro-fuzzy filtering technique in the time domain is proposed. Architecture of neural networks is shown having the purpose of exploiting spatial information, with the advantage of little computational load with respect to other classical beamforming techniques. Several results are described for complex acoustic scenarios with VOX ASR system by DIBE (University of Genova).
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
用于自动语音识别增强的神经模糊滤波技术
为了提高自动语音识别系统的单词识别率,提出了一种时域自适应神经模糊滤波技术。神经网络结构具有利用空间信息的目的,相对于其他经典波束形成技术具有计算量小的优点。用DIBE(热那亚大学)的VOX ASR系统描述了几种复杂声学场景的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Remote data transfer in distributed measurement, diagnostics and control systems Neuro-fuzzy filtering techniques for automatic speech recognition enhancement Fuzzy classification of image pixels Synchronization of sampling in distributed signal processing systems Systematic VHDL code generation using pipeline operations produced by high level synthesis
×
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