Word Embedding for Emotional Analysis: An Overview

MohammadiBaghmolaei, Rezvan; Ahmadi, Ali

doi:10.1109/icee50131.2020.9260585

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Figure 5 Schematic Diagram Of Word Embedded Sentiment Analysis1

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Cited by 5 publications

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“…The same operation is then performed for the remaining three words. Finally, the classifier is constructed using the averaging method, averaged over them, and then transferred to the softmax classifier, which outputs the predictions [18]. Although the averaging method gives a better prediction, what it does is average the meanings of all the words in the example.…”

Section: Figure 5 Schematic Diagram Of Word Embedded Sentiment Analysismentioning

confidence: 99%

A Study of Speech Recognition with Deep Learning

Li¹

2022

IJMRA

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The development of deep learning and the continuous progress of artificial intelligence have contributed to the rapid development of speech recognition. Among them, the end-to-end structure is the more important part of the whole speech recognition. This paper introduces two end-to-end speech recognition methods, the attention model and the CTC loss function, describes the practical application of deep learning in speech recognition and suggests improvements to the two models. Finally, the practical usefulness of speech recognition is demonstrated by analyzing the application of trigger word detection and sentiment analysis in artificial intelligence in teaching and learning.

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Section: Figure 5 Schematic Diagram Of Word Embedded Sentiment Analysismentioning

confidence: 99%