Multidimensional feature diversity based speech signal acquisition

Konduru, Ashok Kumar; Iqbal, J. L. Mazher

doi:10.1007/s10772-020-09736-5

Cited by 4 publications

(1 citation statement)

References 34 publications

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“…ese two beamforming modes use MVDR beamforming and SDBF methods, respectively. Next, two screening methods were used, one was after Zelinski and the other was after McCowan, to further filter the interventions and conduct a simulation system experiment [9]. rough the built-in Pocket sphinx speech recognition test in the Ubuntu system, the MVDR and SDBF beam methods have been proven to effectively improve the performance of the remote speakers, and beamforming and filtering have been proven to have better system performance [10].…”

Section: Related Workmentioning

confidence: 99%

Application of Abnormal Network Traffic Classification in the Teaching System of Distance Political Course

2022

Mobile Information Systems

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Based on the method of the abnormal network traffic classification system of the CNN network, the traffic is encrypted according to the split and capture strategy, which makes it difficult to find the most important value in the whole world. An unconventional network is proposed based on CNN. This method combines several substeps, such as image creation, image selection, sorting, and end-to-end structure, and automatic learning of indirect relations is detected from the required original input and output, and it is possible applicable globally. The ideology of the ideological and political courses and political system of these distance universities is aimed at ensuring the political direction of college students and ensuring a comprehensive understanding of socialism in order to effectively conduct higher education courses. The ideological and political courses of a certain college have different characteristics from other courses. The teaching system provides students with an independent learning environment. Students can use the courses, teaching materials, text, drawings, and video information provided by the system to deepen their understanding and application knowledge.

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Section: Related Workmentioning

confidence: 99%

Application of Abnormal Network Traffic Classification in the Teaching System of Distance Political Course

2022

Mobile Information Systems

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Voice-based Gender and Age Recognition System

Kone,

Anagal,

Anegundi

et al. 2023

2023 International Conference on Advancement in Computation &Amp; Computer Technologies (InCACCT)

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Computer Speech Recognition Technology and Graphic Shape Design

Niu¹

2022

Advances in Multimedia

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In order to solve the problem of lack of multimodal emotional database, a computer speech recognition technology and graphic form design research were proposed. Using the hidden Markov model (HMM) to recognize speech emotion is mainly to provide emotion type for the subsequent expression fusion. When the emotion category in the speech is obtained, the facial animation parameter (FAP) corresponding to the speech emotion can be combined with the lip movement FAP based on the Moving Pictures Experts Group (MPEG-4) face animation standard to obtain a comprehensive FAP. The results show that the recognition effect of speech emotion recognition in the method used in this paper is relatively better than that obtained by other literature methods, and the average recognition rate reaches 70.24%, which is higher than the other three methods. It is verified that this method can present a better recognition effect.

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Multidimensional feature diversity based speech signal acquisition

Cited by 4 publications

References 34 publications

Application of Abnormal Network Traffic Classification in the Teaching System of Distance Political Course

Application of Abnormal Network Traffic Classification in the Teaching System of Distance Political Course

Voice-based Gender and Age Recognition System

Computer Speech Recognition Technology and Graphic Shape Design

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