Research and application of hidden Markov model in data mining

Author(s):  
Zhang Youzhi
Author(s):  
Yuansheng Zeng

In order to further improve the teaching quality evaluation accuracy of physical education(abbreviated as PE) curriculum in colleges, this study conducts an in-deep research on the overall evaluation of PE teaching effect in colleges from the aspects of teachers’ teaching ability and students’ learning effect based on the hybrid technology of data mining and hidden Markov model. First of all, this study analyzes the development status of the teaching quality evaluation system of PE curriculum in colleges; Secondly, it analyzes the applicability of data mining technology and hidden Markov model to the evaluation of PE teaching quality in colleges, and proposes a mathematical model for evaluating the quality of PE teaching in colleges; Finally, this study carries out a series of experiments on the basis of mathematical models, and analyzes the experimental results in depth. The experimental analysis shows that the model proposed in this paper is helpful to improve the accuracy of PE teaching quality evaluation in colleges. The research results of this study provide a useful exploration for the integration of computing technology and language teaching. At the same time, it provides a reference path and implementation model for improving the teaching of PE for graduates in colleges through machine learning technology.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 34609-34619 ◽  
Author(s):  
Shixiang Lu ◽  
Guoying Lin ◽  
Hanlin Liu ◽  
Chengjin Ye ◽  
Huakun Que ◽  
...  

2012 ◽  
Vol 132 (10) ◽  
pp. 1589-1594 ◽  
Author(s):  
Hayato Waki ◽  
Yutaka Suzuki ◽  
Osamu Sakata ◽  
Mizuya Fukasawa ◽  
Hatsuhiro Kato

MIS Quarterly ◽  
2018 ◽  
Vol 42 (1) ◽  
pp. 83-100 ◽  
Author(s):  
Wei Chen ◽  
◽  
Xiahua Wei ◽  
Kevin Xiaoguo Zhu ◽  
◽  
...  

2016 ◽  
Vol 7 (2) ◽  
pp. 76-82
Author(s):  
Hugeng Hugeng ◽  
Edbert Hansel

We have built an application of speech recognition for Indonesian geography dictionary based on Android operating system, named GAIA. This application uses a smartphone as a device to receive input in the form of a spoken word from a user. The approach used in recognition is Hidden Markov Model which is contained in the Pocketsphinx library. The phonemes used are Indonesian phonemes’ rule. The advantage of this application is that it can be used without internet access. In the application testing, word detection is done with four conditions to determine the level of accuracy. The four conditions are near silent, near noisy, far silent, and far noisy. From the testing and analysis conducted, it can be concluded that GAIA application can be built as a speech recognition application on Android for Indonesian geography dictionary; with the results in the near silent condition accuracy of word recognition reaches an average of 52.87%, in the near noisy reaches an average of 14.5%, in the far silent condition reaches an average of 23.2%, and in the far noisy condition reaches an average of 2.8%. Index Terms—speech recognition, Indonesian geography dictionary, Hidden Markov Model, Pocketsphinx, Android.


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