Titlebook: Intelligent Human Computer Interaction; 14th International C Hakimjon Zaynidinov,Madhusudan Singh,Dhananjay Sin Conference proceedings 2023

congenial

溫順

Automatic Speech Recognition on the Neutral Network Based on Attention Mechanism,d neural network model based on attention mechanism, which are widely used in automatic speech recognition, have been proposed, which are taught on the basis of Uzbek and Russian speech corpuscles and the results obtained are comparatively analyzed.

愉快嗎

Conference proceedings 2023kent, Uzbekistan, during October 20–22, 2022.?.The 47 full papers and 13 short papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: Bio-inspired Computing; Cognitive computing; Human Centered AI; Intelligent Techn

欺騙世家

asthma

,GWD: Graded Word Drop Model for?When Type Questions for?Hindi QA,he GWD preprocessed text gave improvement over non-preprocessed results in terms of both accuracy and F1-score and achieved 53.57%, 38.09%, 55.95% accuracy, and 63.21, 68.37 and 67.09 F1-score in mBERT, XLM-RoBERTa and MuRIL respectively and improved prediction times by five fold in all these models.

束縛

Masked Face Recognition Model with Explainable AI,ee whether the model has really focused on the regions of interest. Our approach showed through the generated heatmaps that difference in the data of the training models make difference in range of focus.

熱心助人

琺瑯

Uzbek Speech Synthesis Using Deep Learning Algorithms, Tacotron and the neural vocoder parallel waveGAN. The formed speech corpus with the volume of 31?h of Uzbek speech is described. The quality of the synthesized speech was evaluated using the MOS scale, according to that the intelligibility and accuracy of the synthesized speech was 4.36 points out of five.

罐里有戒指

Cumbersome