Dublin, Feb. 16, 2024 (GLOBE NEWSWIRE) -- The "China Automotive Multimodal Interaction Development Research Report, 2023" report has been added to ResearchAndMarkets.com's offering.
China Automotive Multimodal Interaction Development Research Report, 2023 combs through the interaction modes of mainstream cockpits, the application of interaction modes in key vehicle models launched in 2023, the cockpit interaction solutions of suppliers, and the multimodal interaction fusion trends.
Foundation models and multimodal fusion will facilitate the introduction of AI Agent into cars.
Large AI models are evolving from the single-modal to the multi-modal and multi-task fusion. Compared with the single-modal that can only process one type of data such as text, image and speech, the multimodal can process and understand multiple types of data, including vision, hearing and language, thus better understanding and generating complex information.
As multimodal foundation models continue to develop, their capabilities will also be significantly improved. This improvement gives AI Agent higher capabilities of perception and environment understanding to achieve more intelligent, automatic decisions and actions, and also creates new possibilities for its application in automotive, providing a broader prospect for future intelligent development.
Car control by voice extends from inside to outside cars.
Changan Nevo A07 adopts iFlytek's latest technology XTTS 4.0. The voice of the car voice assistant is more natural and anthropomorphic, and can express multiple emotions such as happiness, regret, and confusion. It supports saying towards the outside of the car (the content can be user-defined). In addition, the trunk, windows, music, air conditioning, pull-out/parking and other functions can also be controlled by voice outside the car.
Voiceprint recognition finds wider application.
All Li Auto's L series models support voiceprint recognition function. After passengers register their voiceprints, 'Lixiang Classmate' can identify who the passenger is, call the nicknames designated by different passengers, and perform vehicle control according to the positions of different passengers memorized via their voiceprint.
Myoelectric interaction comes into commercial use in cars.
In April 2023, Voyah Passion and FlectoThink introduced a myoelectric interaction fusion solution enabled through a myoelectric bracelet. A multi-channel myoelectric sensor and a high-precision amplifier that are installed inside the bracelet can collect rich myoelectric signals in real time and generate algorithms, and transmit them to the computing terminal to generate a personalized AI gesture model, which is then integrated with Voyah's vehicle platforms.
Multimodal fusion creates active interaction.
Currently multimodal fusion enabled by automakers includes but is not limited to voice + lip motion recognition, voice + face recognition, voice + gesture recognition, voice + head posture, face + emotion recognition, face + eye tracking, and fragrance + face + voice recognition. Wherein multimodal voice interaction is mainstream, and supports models mentioned above, like Changan Nevo A07, Jiyue 01, Li L7, and Hycan A06/V09.
Key Topics Covered:
1 Overview of Multimodal Interaction
1.1 Definition of Multimodal Interaction
1.2 Multimodal Interaction Industry Chain
1.2.1 Multimodal Interaction Industry Chain - Chip Vendors
1.2.2 Multimodal Interaction Industry Chain - Algorithm Providers
1.2.3 Multimodal Interaction Industry Chain - System Integrators
1.3 Multimodal Fusion Algorithms
1.3.1 Speech Algorithm
1.3.2 Vision Algorithm
1.4 Multimodal Interaction Policy Environment
1.4.1 Policy and Regulation Environment
1.4.2 Multimodal Interaction Laws and Regulations
1.4.3 In-cabin Information Security Strategies of OEMs
2 Human-Computer Interaction Based on Touch
2.1 Haptic Interaction Development Route
2.2 Highlights of Haptic Interaction of OEMs
2.3 Cockpit Display Trends
2.4 Development Trends of Smart Surface Materials
2.5 Haptic Feedback Mechanism
3 Human-Computer Interaction Based on Hearing
3.1 Voice Function Development Route
3.2 Summary on Voice Functions of OEMs
3.3 Summary on OTA Updates on Voice Functions of OEMs
3.4 Development Trends of Voice Interaction Images
3.5 Application of Voiceprint Recognition in Car Models
3.6 Customization Trends of Voice Functions
3.7 Major Suppliers of Voice Functions
3.8 Voice Function Development Models of OEMs
4 Human-Computer Interaction Based on Vision
4.1 Face Recognition
4.1.1 Face Recognition Function Development Route
4.1.2 Application of Face Recognition in Car Models
4.1.3 Summary on Face Recognition Suppliers
4.2 Gesture Recognition
4.2.1 Gesture Recognition Function Development Route
4.2.2 Application of Gesture Recognition in Car Models
4.2.3 Summary on Gesture Recognition Suppliers
4.3 Lip Movement Recognition
4.3.1 Lip Movement Recognition Function Development Route
4.3.2 Application of Lip Motion Recognition in Car Models
4.3.3 Summary on Lip Movement Recognition Suppliers
4.4 Other Visual Interaction
4.4.1 AR/VR Interaction Function Development Route
4.4.2 Application of AR/VR Interaction in Car Models
4.4.3 Summary on AR/VR Interaction Suppliers
5 Human-Computer Interaction Based on Smell
5.1 Olfactory Interaction Function Development Route
5.2 Principle of Intelligent Fragrance System
5.3 Fragrance System Technology
5.4 Application of Olfactory Interaction in Car Models
5.5 Summary on Fragrance System Technologies of OEMs
5.6 Olfactory Interaction Design Trends
5.7 Summary on Olfactory Interaction Suppliers
6 Human-Computer Interaction Based on Biometrics
6.1 Fingerprint Recognition
6.1.1 Fingerprint Recognition Function Development Route
6.1.2 Application of Fingerprint Recognition in Car Models
6.1.3 Summary on Fingerprint Recognition Suppliers
6.2 Iris Recognition
6.2.1 Iris Recognition Function Development Route
6.2.2 Application of Iris Recognition in Car Models
6.2.3 Application of Iris Recognition in AR/VR
6.2.4 Summary on Iris Recognition Suppliers
6.3 Myoelectric Recognition
6.3.1 Myoelectric Recognition Function Development Route
6.3.2 Application of Myoelectric Recognition in Car Models
6.3.3 Introduction to Myoelectric Recognition Equipment
6.3.4 Summary on Myoelectric Recognition Suppliers
6.4 Vein Recognition
6.4.1 Vein Recognition Function Development Route
6.4.2 Application of Vein Recognition in Car Models
6.4.3 Summary on Vein Recognition Suppliers
6.5 Heart Rate Recognition
6.5.1 Heart Rate Recognition Function Development Route
6.5.2 Heart Rate Recognition Technology
6.5.3 Application of Heart Rate Recognition in Car Models
7 Multimodal Interaction Application by OEMs
7.1 Emerging Carmakers
7.1.1 Multimodal Interaction in Xpeng G6
7.1.2 Multimodal Interaction in Li L7
7.1.3 Multimodal Interaction in NIO EC7
7.1.4 Multimodal Interaction in Neta GT
7.1.5 Multimodal Interaction in HiPhi Y
7.1.6 Multimodal Interaction in Hycan A06
7.1.7 Multimodal Interaction in Hycan V09
7.1.8 Multimodal Interaction in New AITO M7
7.1.9 Multimodal Interaction in AITO M9
7.2 Conventional Chinese Independent Automakers
7.2.1 Multimodal Interaction in Chery Cowin Kunlun
7.2.2 Multimodal Interaction in WEY Blue Mountain DHT PHEV
7.2.3 Multimodal Interaction in Hyper GT
7.2.4 Multimodal Interaction in Trumpchi E9
7.2.5 Multimodal Interaction in Voyah Passion
7.2.6 Multimodal Interaction in Denza N7
7.2.7 Multimodal Interaction in Frigate 07
7.2.8 Multimodal Interaction in Changan Nevo A07
7.2.9 Multimodal Interaction in Jiyue 01
7.2.10 Multimodal Interaction in ARCFOX Kaola
7.2.11 Multimodal Interaction in Deepal S7
7.2.12 Multimodal Interaction in Galaxy L6
7.2.13 Multimodal Interaction in Lynk & Co 08
7.2.14 Multimodal Interaction in LIVAN 7
7.2.15 Multimodal Interaction in ZEEKR X
7.2.16 Multimodal Interaction in ZEEKR 009
7.2.17 Multimodal Interaction in IM LS7
7.2.18 Multimodal Interaction in GEOME G6
7.3 Conventional Joint Venture Automakers
7.3.1 Multimodal Interaction in Mercedes-Benz EQS AMG
7.3.2 Multimodal Interaction in GAC Toyota bZ 4X
7.3.3 Multimodal Interaction in FAW Toyota bZ 3
7.3.4 Multimodal Interaction in Buick Electra E5
7.3.5 Multimodal Interaction in 11th Generation GAC Honda Accord
7.3.6 Multimodal Interaction in FAW Audi e-tron GT
7.3.7 Multimodal Interaction in BMW XM
7.4 Concept Cars
7.4.1 Multimodal Interaction in Audi A6 Avant e-tron
7.4.2 Multimodal Interaction in BMW i Vision Dee
7.4.3 Multimodal Interaction in RAM 1500 Revolution
7.4.4 Multimodal Interaction in Peugeot Inception
7.4.5 Multimodal Interaction in Yanfeng XiM23s
8 Multimodal Interaction Solutions of Suppliers
8.1 Aptiv
8.2 Cipia Vision
8.3 Cerence
8.4 Continental
8.5 iFlytek
8.6 SenseTime
8.7 ADAYO
8.8 Desay SV
8.9 ArcSoft Technology
8.10 AISpeech
8.11 Horizon Robotics
8.12 ThunderSoft
8.13 PATEO
8.14 Joyson Electronics
8.15 Huawei
8.16 Baidu
8.17 Tencent
8.18 Banma Network
8.19 MINIEYE
8.20 Hikvision
8.20.3 Vehicle Intelligent Monitoring System
9 Multimodal Interaction Summary and Trends
9.1 Multimodal Interaction Fusion Trends
9.1.1 Development of Intelligent Cockpit Interaction System
9.1.2 Development Trends of Single-modal Perception - Touch
9.1.3 Development Trends of Single-modal Perception - Hearing
9.1.4 Development Trends of Single-modal Perception - Vision
9.1.5 Development Trends of Single-modal Perception - Smell
9.1.6 Multimodal Interaction Fusion Trends
9.1.7 Multimodal Interaction Development Roadmap
9.2 Cockpit Computing Power Required by Multimodal Interaction
9.3 Large AI Models Required by Multimodal Interaction
9.4 Integration of Multimodal Interaction and Cockpit Hardware
9.4.1 Multimodal Recognition and Hardware Interaction - Headlights
9.4.2 Multimodal Recognition and Hardware Interaction - Ambient Light
9.4.3 Multimodal Recognition and Hardware Interaction - AR/VR
9.5 Summary on Multimodal Interaction Features in Typical Car Models
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