Child intention and sentiment analysis method and system

Abstract

The embodiment of the invention provides a child intention and sentiment analysis method and system. The child intention and sentiment analysis method comprises the steps that front-end equipment collects the audio information of a child, and transmits the audio information to a rear-end server; the back-end server captures audio data in the audio information at preset time intervals; the rear-endserver selects a child language habit model according to the audio data to complete voice analysis of the child; and the back-end server obtains a child intention and sentiment analysis result according to the voice analysis result. By adopting the technical scheme of the invention, the interaction effect between the child user and the intelligent equipment can be improved, and the accuracy of child intention and sentiment analysis is improved.

Description

technical field [0001] The invention relates to the technical field of smart devices, in particular to a method and system for analyzing children's intentions and emotions. Background technique [0002] The current intent understanding and sentiment analysis based on speech recognition and natural language understanding (NLP) have achieved a certain degree of accuracy for the speech input of adult users, but it is difficult for the existing technology to play a better role in semantic understanding when facing children. The function of good intention and sentiment analysis is because children have completely different pronunciation patterns from adults, and children are limited by the degree of language and cognitive development, and often cannot use and adjust their own expressions to meet the needs of voice interaction. Limited by the development of speech recognition technology, it is currently difficult to solve the problem of semantic understanding from the level of imp...

AI Technical Summary

Problems solved by technology

[0002] The current intent understanding and sentiment analysis based on speech recognition and natural language understanding (NLP) have achieved a certain degree of accuracy for the speech input of adult users, but it is difficult for the existing technology to play a better role in semantic understanding when facing children. The function of good intention and sentiment analysis, because children have completely different pronunciation patterns from adults, and children are limited by the degree of language and cognitive development, and often cannot use and adjust their own expressions to meet the needs of voice interaction

Limited by the development of speech recognition technology, it is currently difficult for children to solve the problem of semantic understanding from the level of improving the accuracy of speech recognition, and there is still no more accurate method for understanding intentions and sentiment analysis suitable for children

Images