TY - GEN
T1 - MCU-based isolated appealing words detecting method with AI techniques
AU - Ye, Liang
AU - Li, Yue
AU - Dong, Wenjing
AU - Seppänen, Tapio
AU - Alasaarela, Esko
N1 - Publisher Copyright:
© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019 Published by Springer Nature Switzerland AG 2019. All Rights Reserved.
PY - 2019
Y1 - 2019
N2 - Bullying in campus has attracted more and more attention in recent years. By analyzing typical campus bullying events, it can be found that the victims often use the words “help” and some other appealing or begging words, that is to say, by using the artificial intelligence of speech recognition, we can find the occurrence of campus bullying events in time, and take measures to avoid further harm. The main purpose of this study is to help the guardians discover the occurrence of campus bullying in time by real-time monitoring of the keywords of campus bullying, and take corresponding measures in the first time to minimize the harm of campus bullying. On the basis of Sunplus MCU and speech recognition technology, by using the MFCC acoustic features and an efficient DTW classifier, we were able to realize the detection of common vocabulary of campus bullying for the specific human voice. After repeated experiments, and finally combining the voice signal processing functions of Sunplus MCU, the recognition procedure of specific isolated words was completed. On the basis of realizing the isolated word detection of specific human voice, we got an average accuracy of 99% of appealing words for the dedicated speaker and the misrecognition rate of other words and other speakers was very low.
AB - Bullying in campus has attracted more and more attention in recent years. By analyzing typical campus bullying events, it can be found that the victims often use the words “help” and some other appealing or begging words, that is to say, by using the artificial intelligence of speech recognition, we can find the occurrence of campus bullying events in time, and take measures to avoid further harm. The main purpose of this study is to help the guardians discover the occurrence of campus bullying in time by real-time monitoring of the keywords of campus bullying, and take corresponding measures in the first time to minimize the harm of campus bullying. On the basis of Sunplus MCU and speech recognition technology, by using the MFCC acoustic features and an efficient DTW classifier, we were able to realize the detection of common vocabulary of campus bullying for the specific human voice. After repeated experiments, and finally combining the voice signal processing functions of Sunplus MCU, the recognition procedure of specific isolated words was completed. On the basis of realizing the isolated word detection of specific human voice, we got an average accuracy of 99% of appealing words for the dedicated speaker and the misrecognition rate of other words and other speakers was very low.
KW - AI
KW - Appealing words detection
KW - MCU
KW - Speech recognition
UR - https://www.scopus.com/pages/publications/85069209093
U2 - 10.1007/978-3-030-22971-9_26
DO - 10.1007/978-3-030-22971-9_26
M3 - 会议稿件
AN - SCOPUS:85069209093
SN - 9783030229702
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 300
EP - 308
BT - Artificial Intelligence for Communications and Networks - 1st EAI International Conference, AICON 2019, Proceedings
A2 - Han, Shuai
A2 - Ye, Liang
A2 - Meng, Weixiao
PB - Springer Verlag
T2 - 1st EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2019
Y2 - 25 May 2019 through 26 May 2019
ER -