用于多模态交互服务和应用程序的基于云的中间件

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Bilgin Avenoglu, V. J. Koeman, K. Hindriks
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引用次数: 0

摘要

智能设备,如智能手机、语音助手和社交机器人,为用户提供一系列输入方式,如语音、触摸、手势和视觉。近年来,这些输入通道处理的进步为用户提供了更自然的交互体验(例如,自动语音,面部和手势识别,对话生成,情感表达等)。然而,要创造这些用户体验,有几个重要的挑战需要解决。一个挑战是,大多数智能设备没有足够的计算资源来本地执行人工智能(AI)技术。另一个挑战是,当用户与这些设备交互时,他们希望得到近乎实时的响应。此外,用户还希望能够随时随地在设备和服务之间无缝切换,并期望个性化和隐私意识服务。为了应对这些挑战,我们设计并开发了一个基于云的中间件(CMI),它有助于开发多模态交互应用程序,并轻松地将应用程序集成到人工智能服务中。在这个中间件中,可以很容易地集成由具有不同协议的不同生产者开发的服务和具有不同功能和协议的智能设备。在CMI中,应用程序将数据从设备流到云服务进行处理并使用结果。它支持从多个设备到多个服务的数据流(反之亦然)。CMI提供了一个集成框架,用于解耦服务和设备,并使应用程序开发人员能够专注于“交互”而不是人工智能技术。我们提供简单的例子来说明CMI中包含的概念思想。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A cloud-based middleware for multi-modal interaction services and applications
Smart devices, such as smart phones, voice assistants and social robots, provide users with a range of input modalities, e.g., speech, touch, gestures, and vision. In recent years, advancements in processing of these input channels enable more natural interaction (e.g., automated speech, face, and gesture recognition, dialog generation, emotion expression etc.) experiences for users. However, there are several important challenges that need to be addressed to create these user experiences. One challenge is that most smart devices do not have sufficient computing resources to execute the Artificial Intelligence (AI) techniques locally. Another challenge is that users expect responses in near real-time when they interact with these devices. Moreover, users also want to be able to seamlessly switch between devices and services any time and from anywhere and expect personalized and privacy-aware services. To address these challenges, we design and develop a cloud-based middleware (CMI) which helps to develop multi-modal interaction applications and easily integrate applications to AI services. In this middleware, services developed by different producers with different protocols and smart devices with different capabilities and protocols can be integrated easily. In CMI, applications stream data from devices to cloud services for processing and consume the results. It supports data streaming from multiple devices to multiple services (and vice versa). CMI provides an integration framework for decoupling the services and devices and enabling application developers to concentrate on “interaction” instead of AI techniques. We provide simple examples to illustrate the conceptual ideas incorporated in CMI.
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来源期刊
Journal of Ambient Intelligence and Smart Environments
Journal of Ambient Intelligence and Smart Environments COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
4.30
自引率
17.60%
发文量
23
审稿时长
>12 weeks
期刊介绍: The Journal of Ambient Intelligence and Smart Environments (JAISE) serves as a forum to discuss the latest developments on Ambient Intelligence (AmI) and Smart Environments (SmE). Given the multi-disciplinary nature of the areas involved, the journal aims to promote participation from several different communities covering topics ranging from enabling technologies such as multi-modal sensing and vision processing, to algorithmic aspects in interpretive and reasoning domains, to application-oriented efforts in human-centered services, as well as contributions from the fields of robotics, networking, HCI, mobile, collaborative and pervasive computing. This diversity stems from the fact that smart environments can be defined with a variety of different characteristics based on the applications they serve, their interaction models with humans, the practical system design aspects, as well as the multi-faceted conceptual and algorithmic considerations that would enable them to operate seamlessly and unobtrusively. The Journal of Ambient Intelligence and Smart Environments will focus on both the technical and application aspects of these.
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