Interactive artificial intelligence driven face and voice analysis method and system

Through interactive artificial intelligence-driven facial and voice analysis methods, real-time acquisition and analysis of driver's facial images and voice data, identify emotional states and automatically adjust the interior environment, solving the shortcomings of the existing system in response to drivers' emotions and improving driving experience and safety.

CN119705326AActive Publication Date: 2025-03-28HEALTH HOPE (BEIJING) TECH CO LTD
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Patent Information

Application Number
CN202411823953.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-12
Publication Date
2025-03-28
Estimated Expiration
2044-12-12

AI Technical Summary

Technical Problem

Existing vehicle interaction systems have shortcomings in understanding and responding to driver emotional states, especially in automotive environments where facial image and voice data acquisition is challenged, and there is a lack of dynamic response mechanisms to adjust the in-vehicle environment to relieve driver emotions.

Method used

The facial and speech analysis method driven by interactive artificial intelligence is adopted to emotionally recognize facial image data and speech data through deep learning models, obtain user's emotional state information, and automatically adjust the interior environment in the car, including parameters such as temperature and humidity based on this information.

Benefits of technology

Real-time and accurate judgment of the driver's emotional state, and automatically adjust the interior environment according to the emotional state, improving the driving experience, reducing driving risks, and promoting the car to develop in a more intelligent and personalized direction.

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Abstract

The invention provides a face and voice analysis method and system driven by interactive artificial intelligence. The interactive artificial intelligence driven face and voice analysis method comprises the following steps: collecting face image data of a user according to a current vehicle driving state, and obtaining the face image data of the user in a vehicle; voice data of a user is collected according to the current vehicle driving state, and voice data in the vehicle is obtained; performing emotion recognition processing on the facial image data and the voice data through a deep learning model to obtain current emotion state information of the user; feeding back the current emotional state information of the user to a vehicle interaction system; and the vehicle interaction system calls the in-vehicle environment parameter scheme matched with the current emotional state of the user from a database, and adjusts the in-vehicle environment according to the in-vehicle environment parameter scheme. The system comprises modules corresponding to the steps of the method.
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