With the rapid development of English, people's requirements for the level of speech information processing are constantly increasing. However, some errors that cannot be accurately identified often occur in pract...
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With the development of information technology, computer technology is also gradually applied to the teaching activities of art education, and the use of multimedia technology to assist music teaching has become one o...
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With the development of information technology, computer technology is also gradually applied to the teaching activities of art education, and the use of multimedia technology to assist music teaching has become one of the hot research areas in universities. In order to better cultivate university students' musical exploration ability and creativity, a music note feature recognition teaching model based on Hidden Markov Model (hmm) algorithm is studied and optimized in universities by using genetic algorithm based on hmm algorithm. The music note feature recognition teaching model studied in this article combines computer multimedia technology, signal processing technology, and music theory, and uses computers to simulate the process of human cognition and analysis of music. And in this article, a music note recognition system was constructed using the features of sound level contours combined with the hmm algorithm. The data extracted during music recognition was compressed using the energy compression feature of sound level contours. At the same time, maximum likelihood estimation was used to find the optimal chord sequence, i.e., the optimal path, for the input signal. In the experimental results, the minimum value of the objective function was about 0.739 when the variance probability and crossover probability were 0.02 and 0.6, respectively. In the results, the hmm algorithm-based music note recognition model can improve the quality of music teaching and has some potential for application in the field of music teaching.
Voice recognition and command technology for applications with industrial robots is a relatively new field in the intelligent manufacturing industry. It offers a number of advantages over other methods of communicatio...
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ISBN:
(纸本)9781665489218
Voice recognition and command technology for applications with industrial robots is a relatively new field in the intelligent manufacturing industry. It offers a number of advantages over other methods of communication with robots, as it requires fewer specialized skills to manipulate the robot workstation. Additionally, using voice commands can help reduce the number of industrial injuries caused by contact with machinery, thus potentially save operators' lives in emergency situations where external assistance is not immediately available. This study presents a design of a Cartesian robot workstation which is equipped with a voice recognition system controlled by audio commands, as well as a vision perception system. The vision perception system uses the Real Sense depth camera that captures information about the coordinates of the work pieces, which is processed by SSD algorithm. The voice recognition system has been developed with an algorithm which combines both LSTM and hmm, and it has good performance in term of both efficiency and accuracy in controlling normal operation as well as emergency stop for our robot grasping workstation.
In cold boot attacks, attackers attempt to retrieve encryption keys from the memory after the system is powered off. One representative cold boot attack, known as hmm algorithm, can break RSA with success probabilitie...
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ISBN:
(纸本)9781538614211
In cold boot attacks, attackers attempt to retrieve encryption keys from the memory after the system is powered off. One representative cold boot attack, known as hmm algorithm, can break RSA with success probabilities as high as 82% However, it, like other cold boot attacks, uses the symmetric memory decay model, which assumes that a bit is equally likely to change from 1 to 0 and from 0 to 1. It also requires that the bit error probability to be relatively small, which means that the attack must be launched within seconds of system power off. In this paper, we first show that under more realistic assumptions, ILVILVI's success probability drops to 2.3% We then propose a practical improvement of hmm algorithm with a proven lower bound on success probability and low runtime complexity. We conduct simulation and the results confirm that our approach improves ILVILVI's chance of breaking RSA to 49.96%
Due to the increase in globalization, communication between different countries has become more and more frequent. Language barriers are the most important issues in communication. Machine translation is limited to te...
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Due to the increase in globalization, communication between different countries has become more and more frequent. Language barriers are the most important issues in communication. Machine translation is limited to texts, and cannot be an adequate substitute for oral communication. In this study, a speech recognition and translation system based on embedded technology was developed for the purpose of English speech recognition and translation. The system adopted the Hidden Markov Model (hmm) and Windows CE operating system. Experiments involving English speech recognition and English-Chinese translation found that the accuracy of the system in identifying English speech was about 88%, and the accuracy rate of the system in translating English to Chinese was over 85%. The embedded technology-based English speech recognition and translation system demonstrated a level of high accuracy in speech identification and translation, demonstrating its value as a practical application. Therefore, it merits further research and development.
Leisure hotels, as the core and important carrier of tourism development, are facing a broad development opportunity with the intervention of artificial intelligence. This paper designs a speech recognition system usi...
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According to the problem of the low recognition rate of speaker-independent recognition in intelligent robot, a kind of endpoint detection algorithm with double threshold is adopted and the speech endpoint can be dete...
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ISBN:
(纸本)9781424441990
According to the problem of the low recognition rate of speaker-independent recognition in intelligent robot, a kind of endpoint detection algorithm with double threshold is adopted and the speech endpoint can be detected accurately. The mixed parameter of Mel Frequency Cepstral Coefficients (MFCC) and fractal dimension is used as the feature parameter, and the intelligent robot command-word recognition system based on Hidden Markov Models (hmm) is realized. The recognition effect achieves above 85%. Then the performance of MFCC and the mixed parameter of MFCC and fractal dimension is contrasted and analyzed. The experiment result shows that the system recognition rate is improved by the algorithm of mixed parameter, and the system recognition performance is optimized.
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