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Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks

This paper constructs knowledge graphs of speech emotion feature to support the expression of rich semantic information due to their unique graphical structure and to provide new ideas for studying speech emotion recognition recommendations. Impulse-coupled neural networks, as a mathematical abstrac...

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Autor principal: Song, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286990/
https://www.ncbi.nlm.nih.gov/pubmed/35845880
http://dx.doi.org/10.1155/2022/8766145
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author Song, Yan
author_facet Song, Yan
author_sort Song, Yan
collection PubMed
description This paper constructs knowledge graphs of speech emotion feature to support the expression of rich semantic information due to their unique graphical structure and to provide new ideas for studying speech emotion recognition recommendations. Impulse-coupled neural networks, as a mathematical abstraction of the visual properties of the human eye, have been widely used in various fields of speech processing. In this paper, we take the classical impulse-coupled neural network model as the research object, aiming to explore, analyze, and study the method of constructing knowledge maps of speech emotion features based on the impulse-coupled neural network model, and propose several improved impulse-coupled neural network models, which are used in the fields of target detection, speech segmentation, and quantization compression. This paper further constructs various domain semantic concept maps and performs multidimensional semantic enhancement understanding of search text based on the concept maps and the constructed entity-relationship knowledge maps and proposes a knowledge-based interpretable recommendation method for cloud services and a generalized recommendation and sample enhancement method for cloud scenarios. The fusion algorithm based on multiscale analysis can decompose the source speech into subspeech at different scales and then fuse each subspeech separately, while typical objects in the real world are also composed of many components at different scales. Based on the factors of different degrees in the speech context, the imagery work ruler evaluation model is refined with the basic principles of risk perception and risk resolution in the context, and an exploratory design is carried out separately for the verbal description, graphics, text, color, animation, and sound signals in the audiovisual signal using the workshop format to obtain a large number of design samples and evaluate the important units in turn, finally integrating the context involved in the study. The perceptual design system is given as a specific contextual design method.
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spelling pubmed-92869902022-07-16 Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks Song, Yan Comput Intell Neurosci Research Article This paper constructs knowledge graphs of speech emotion feature to support the expression of rich semantic information due to their unique graphical structure and to provide new ideas for studying speech emotion recognition recommendations. Impulse-coupled neural networks, as a mathematical abstraction of the visual properties of the human eye, have been widely used in various fields of speech processing. In this paper, we take the classical impulse-coupled neural network model as the research object, aiming to explore, analyze, and study the method of constructing knowledge maps of speech emotion features based on the impulse-coupled neural network model, and propose several improved impulse-coupled neural network models, which are used in the fields of target detection, speech segmentation, and quantization compression. This paper further constructs various domain semantic concept maps and performs multidimensional semantic enhancement understanding of search text based on the concept maps and the constructed entity-relationship knowledge maps and proposes a knowledge-based interpretable recommendation method for cloud services and a generalized recommendation and sample enhancement method for cloud scenarios. The fusion algorithm based on multiscale analysis can decompose the source speech into subspeech at different scales and then fuse each subspeech separately, while typical objects in the real world are also composed of many components at different scales. Based on the factors of different degrees in the speech context, the imagery work ruler evaluation model is refined with the basic principles of risk perception and risk resolution in the context, and an exploratory design is carried out separately for the verbal description, graphics, text, color, animation, and sound signals in the audiovisual signal using the workshop format to obtain a large number of design samples and evaluate the important units in turn, finally integrating the context involved in the study. The perceptual design system is given as a specific contextual design method. Hindawi 2022-07-08 /pmc/articles/PMC9286990/ /pubmed/35845880 http://dx.doi.org/10.1155/2022/8766145 Text en Copyright © 2022 Yan Song. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Song, Yan
Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks
title Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks
title_full Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks
title_fullStr Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks
title_full_unstemmed Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks
title_short Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks
title_sort construction of a knowledge map of speech emotion features based on impulse-coupled neural networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286990/
https://www.ncbi.nlm.nih.gov/pubmed/35845880
http://dx.doi.org/10.1155/2022/8766145
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