基于STM32的嵌入式语音识别模块实现

Qinglin Qu, Liangguang Li
{"title":"基于STM32的嵌入式语音识别模块实现","authors":"Qinglin Qu, Liangguang Li","doi":"10.1109/ISCIT.2011.6092186","DOIUrl":null,"url":null,"abstract":"Speech recognition is the key to realize man-machine interface technology. In order to improve the accuracy of speech recognition and implement the module on embedded system, an embedded speaker-independent isolated word speech recognition system based on ARM is designed after analyzing speech recognition theory. The system uses DTW algorithm and improves the algorithm using a parallelogram to extract characteristic parameters and identify the results. To finish the speech recognition independently, the system uses the STM32 series chip combined with the other external circuitry. The results of speech recognition test can achieve 90%, and which meets the real-time requirements of recognition.","PeriodicalId":226552,"journal":{"name":"2011 11th International Symposium on Communications & Information Technologies (ISCIT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Realization of embedded speech recognition module based on STM32\",\"authors\":\"Qinglin Qu, Liangguang Li\",\"doi\":\"10.1109/ISCIT.2011.6092186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Speech recognition is the key to realize man-machine interface technology. In order to improve the accuracy of speech recognition and implement the module on embedded system, an embedded speaker-independent isolated word speech recognition system based on ARM is designed after analyzing speech recognition theory. The system uses DTW algorithm and improves the algorithm using a parallelogram to extract characteristic parameters and identify the results. To finish the speech recognition independently, the system uses the STM32 series chip combined with the other external circuitry. The results of speech recognition test can achieve 90%, and which meets the real-time requirements of recognition.\",\"PeriodicalId\":226552,\"journal\":{\"name\":\"2011 11th International Symposium on Communications & Information Technologies (ISCIT)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 11th International Symposium on Communications & Information Technologies (ISCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCIT.2011.6092186\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 11th International Symposium on Communications & Information Technologies (ISCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCIT.2011.6092186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

摘要

语音识别是实现人机界面技术的关键。为了提高语音识别的精度,并在嵌入式系统上实现该模块,在分析语音识别原理的基础上,设计了一种基于ARM的嵌入式独立于说话人的孤立词语音识别系统。该系统采用DTW算法,并利用平行四边形对算法进行改进,提取特征参数并对结果进行识别。为了独立完成语音识别,系统采用STM32系列芯片结合其他外部电路。语音识别测试结果可以达到90%,满足了识别实时性的要求。
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
Realization of embedded speech recognition module based on STM32
Speech recognition is the key to realize man-machine interface technology. In order to improve the accuracy of speech recognition and implement the module on embedded system, an embedded speaker-independent isolated word speech recognition system based on ARM is designed after analyzing speech recognition theory. The system uses DTW algorithm and improves the algorithm using a parallelogram to extract characteristic parameters and identify the results. To finish the speech recognition independently, the system uses the STM32 series chip combined with the other external circuitry. The results of speech recognition test can achieve 90%, and which meets the real-time requirements of recognition.
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
Opportunistic routing in multi-channel cognitive radio networks Improved roughening algorithm and hardware implementation for particle filter applied to bearings-only tracking A design of smart radio research platform for universal access in a multi-RAT environment Distributed anomaly event detection in wireless networks using compressed sensing Constructing (k, r)-connected dominating sets for robust backbone in wireless sensor networks
×
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