- 对AI和机器学习概念有基本了解
- 熟悉UI/UX设计原则
- 有一些编程经验（Python 较佳）
受众
- UI/UX设计师
- 产品经理
- AI研究人员
多模态接口的人机协作正在通过整合各种通信模态（例如语音、手势、眼动追踪和视觉元素）来改变人们与智能系统互动的方式。
本课程是面向初级到中级UI/UX设计师、产品经理和希望通过多模态人工智能驱动的接口提升用户体验的人工智能研究人员的在线或现场的老师授课的实时培训。
通过本次培训，参与者将能够：
- 了解多模态人工智能的基本原理及其对人机交互的影响。
- 使用人工智能驱动的输入方法设计和原型多模态接口。
- 实现语音识别、手势控制和眼动追踪技术。
- 评估多模态系统的有效性和可用性。
课程格式
- 互动讲座和讨论。
- 大量的练习和实践。
- 在现场实验室环境中进行动手实施。
课程定制选项
- 要请求本课程的定制培训，请联系我们安排。
多模态接口介绍
- 什么是多模态接口？
- 多模态交互的好处和挑战
- 各行各业的现实世界应用
Multimodal AI和人机交互
- 了解以人为中心的人工智能设计
- 推动多模态接口的关键人工智能技术
- 人类与人工智能协作中的心理和认知考虑
Speech Recognition和Natural Language Processing (NLP)
- 语音转文本和文本转语音技术
- 使用OpenAI的Whisper或Mozilla DeepSpeech
- 改善AI驱动的语音交互
手势识别和动作跟踪
- 了解手部跟踪和身体手势
- 在UI设计中实现手势控制
- 开源手势识别库的动手实践
眼动追踪和基于凝视的交互
- 眼动追踪技术简介
- 在可访问性和自适应接口中的用例
- 开发基于视线的输入系统
多模态融合：整合多种输入方法
- 人工智能如何结合语音、手势和视觉
- 构建自适应和个性化的人工智能交互
- 实现无缝多模态体验的最佳实践
原型制作和实现多模态接口
- 设计用户友好的人工智能驱动的接口
- 使用Figma和人工智能工具对多模态交互进行原型设计
- 使用Python和人工智能框架开发现实世界应用程序
测试和评估多模态接口
- 多模态人工智能的可用性测试方法
- 测量用户体验和满意度
- 完善和优化AI驱动的交互
人机交互中的未来趋势Collaboration
- 多模态人工智能和深度学习的进展
- 人机交互的 Emerging 趋势
- 人工智能在用户体验未来中的作用
总结和结论
United Arab Emirates - Human-AI Collaboration with Multimodal Interfaces
Qatar - Human-AI Collaboration with Multimodal Interfaces
Egypt - Human-AI Collaboration with Multimodal Interfaces
Saudi Arabia - Human-AI Collaboration with Multimodal Interfaces
South Africa - Human-AI Collaboration with Multimodal Interfaces
Brasil - Human-AI Collaboration with Multimodal Interfaces
Canada - Human-AI Collaboration with Multimodal Interfaces
中国 - Human-AI Collaboration with Multimodal Interfaces
香港 - Human-AI Collaboration with Multimodal Interfaces
澳門 - Human-AI Collaboration with Multimodal Interfaces
台灣 - Human-AI Collaboration with Multimodal Interfaces
USA - Human-AI Collaboration with Multimodal Interfaces
Österreich - Human-AI Collaboration with Multimodal Interfaces
Schweiz - Human-AI Collaboration with Multimodal Interfaces
Deutschland - Human-AI Collaboration with Multimodal Interfaces
Czech Republic - Human-AI Collaboration with Multimodal Interfaces
Denmark - Human-AI Collaboration with Multimodal Interfaces
Estonia - Human-AI Collaboration with Multimodal Interfaces
Finland - Human-AI Collaboration with Multimodal Interfaces
Greece - Human-AI Collaboration with Multimodal Interfaces
Magyarország - Human-AI Collaboration with Multimodal Interfaces
Ireland - Human-AI Collaboration with Multimodal Interfaces
Luxembourg - Human-AI Collaboration with Multimodal Interfaces
Latvia - Human-AI Collaboration with Multimodal Interfaces
España - Human-AI Collaboration with Multimodal Interfaces
Italia - Human-AI Collaboration with Multimodal Interfaces
Lithuania - Human-AI Collaboration with Multimodal Interfaces
Nederland - Human-AI Collaboration with Multimodal Interfaces
Norway - Human-AI Collaboration with Multimodal Interfaces
Portugal - Human-AI Collaboration with Multimodal Interfaces
România - Human-AI Collaboration with Multimodal Interfaces
Sverige - Human-AI Collaboration with Multimodal Interfaces
Türkiye - Multimodal AI Arayüzleri ile İnsan-Yapay Zeka İlişkileri
Malta - Human-AI Collaboration with Multimodal Interfaces
Belgique - Human-AI Collaboration with Multimodal Interfaces
France - Human-AI Collaboration with Multimodal Interfaces
日本 - Human-AI Collaboration with Multimodal Interfaces
Australia - Human-AI Collaboration with Multimodal Interfaces
Malaysia - Human-AI Collaboration with Multimodal Interfaces
New Zealand - Human-AI Collaboration with Multimodal Interfaces
Philippines - Human-AI Collaboration with Multimodal Interfaces
Singapore - Human-AI Collaboration with Multimodal Interfaces
Thailand - Human-AI Collaboration with Multimodal Interfaces
Vietnam - Human-AI Collaboration with Multimodal Interfaces
India - Human-AI Collaboration with Multimodal Interfaces
Argentina - Human-AI Collaboration with Multimodal Interfaces
Chile - Human-AI Collaboration with Multimodal Interfaces
Costa Rica - Human-AI Collaboration with Multimodal Interfaces
Ecuador - Human-AI Collaboration with Multimodal Interfaces
Guatemala - Human-AI Collaboration with Multimodal Interfaces
Colombia - Human-AI Collaboration with Multimodal Interfaces
México - Human-AI Collaboration with Multimodal Interfaces
Panama - Human-AI Collaboration with Multimodal Interfaces
Peru - Human-AI Collaboration with Multimodal Interfaces
Uruguay - Human-AI Collaboration with Multimodal Interfaces
Venezuela - Human-AI Collaboration with Multimodal Interfaces
Polska - Human-AI Collaboration with Multimodal Interfaces
United Kingdom - Human-AI Collaboration with Multimodal Interfaces
South Korea - Human-AI Collaboration with Multimodal Interfaces
Pakistan - Human-AI Collaboration with Multimodal Interfaces
Sri Lanka - Human-AI Collaboration with Multimodal Interfaces
Bulgaria - Human-AI Collaboration with Multimodal Interfaces
Bolivia - Human-AI Collaboration with Multimodal Interfaces
Indonesia - Human-AI Collaboration with Multimodal Interfaces
Kazakhstan - Human-AI Collaboration with Multimodal Interfaces
Moldova - Human-AI Collaboration with Multimodal Interfaces
Morocco - Human-AI Collaboration with Multimodal Interfaces
Tunisia - Human-AI Collaboration with Multimodal Interfaces
Kuwait - Human-AI Collaboration with Multimodal Interfaces
Oman - Human-AI Collaboration with Multimodal Interfaces
Slovakia - Human-AI Collaboration with Multimodal Interfaces
Kenya - Human-AI Collaboration with Multimodal Interfaces
Nigeria - Human-AI Collaboration with Multimodal Interfaces
Botswana - Human-AI Collaboration with Multimodal Interfaces
Slovenia - Human-AI Collaboration with Multimodal Interfaces
Croatia - Human-AI Collaboration with Multimodal Interfaces
Serbia - Human-AI Collaboration with Multimodal Interfaces
Bhutan - Human-AI Collaboration with Multimodal Interfaces
Nepal - Human-AI Collaboration with Multimodal Interfaces
Uzbekistan - Human-AI Collaboration with Multimodal Interfaces