期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Wi-Wheat+:Contact-free wheat moisture sensing with commodity WiFi based on entropy
1
作者 Weidong Yang Erbo Shen +3 位作者 Xuyu Wang Shiwen Mao Yuehong Gong Pengming Hu 《Digital Communications and Networks》 SCIE CSCD 2023年第3期698-709,共12页
In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,ex... In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,expensive equipment,low accuracy,and difficulty in real-time monitoring.The proposed system is based on Commodity WiFi and is easy to deploy.Leveraging WiFi CSI data,this paper proposes a feature extraction method based on multi-scale and multi-channel entropy.The feasibility and stability of the system are validated through experiments in both Line-Of-Sight(LOS)and Non-Line-Of-Sight(NLOS)scenarios,where ten types of wheat moisture content are tested using multi-class Support Vector Machine(SVM).Compared with the Wi-Wheat system proposed in our prior work,Wi-Wheatþhas higher efficiency,requiring only a simple training process,and can sense more wheat moisture content levels. 展开更多
关键词 Channel state information(CSI) WIFI Multi-scale entropy multi-class support vector machine(SVM) Radio frequency(RF)sensing
下载PDF
An Introduction to the Chinese Speech Recognition Front-End of the NICT/ATR Multi-Lingual Speech Translation System 被引量:3
2
作者 张劲松 Takatoshi Jitsuhiro +2 位作者 Hirofumi Yamamoto 胡新辉 Satoshi Nakamura 《Tsinghua Science and Technology》 SCIE EI CAS 2008年第4期545-552,共8页
This paper introduces several important features of the Chinese large vocabulary continuous speech recognition system in the NICT/ATR multi-lingual speech-to-speech translation system. The features include: (1) a f... This paper introduces several important features of the Chinese large vocabulary continuous speech recognition system in the NICT/ATR multi-lingual speech-to-speech translation system. The features include: (1) a flexible way to derive an information rich phoneme set based on mutual information between a text corpus and its phoneme set; (2) a hidden Markov network acoustic model and a successive state splitting algorithm to generate its model topology based on a minimum description length criterion; and (3) advanced language modeling using multi-class composite N-grams. These features allow a recognition performance of 90% character accuracy in tourism related dialogue with a real time response speed. 展开更多
关键词 Chinese speech recognition mutual information phoneme set design hidden Markov network minimum description length successive state splitting multi-class composite N-grams
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部