Human-to-Object Interaction by Integrating Speech Technology into Radio Frequency Identification Networks

将语音技术集成到射频识别网络中进行人机交互

• 批准号: 283139-2013
• 负责人: Selouani, SidAhmed
• 金额: $ 2.11万
• 依托单位: Université de Moncton
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=548083
• 关键词: Human; Object; Interaction; Integrating; Speech

New research avenues are explored in order to provide a reliable human-to-object interaction by using speech modality and radio frequency identification (RFID) technology. The aim is to integrate speech technology into RFID networks to allow human operators to communicate verbally with RFID devices, RFID-tagged objects and related information systems. The combination of speech and RFID technologies is expected to improve speed, accuracy, ergonomics and safety of numerous manufacturing and business operations such as item tracking and monitoring, warehouse management, and shipping. However, many problems related to the reliability of the speech component remain unsolved and constitute obstacles in the way of the deployment of speech-enabled RFID systems. To insure the efficacy of the proposed RFID-Speech framework in real-life conditions (manufactory and warehouse environment), a very robust real-time speech recognition and a non-constrained and flexible dialogue scheme should be provided. Therefore, our proposed strategy consists of operating at both acoustic and language levels. At the acoustic level, cutting edge algorithms based on bio-inspired approaches (bird flocking and genetic algorithms) are proposed to optimize the estimation and tracking of non-stationary noises. At the language level, the proposed strategy consists of leveraging knowledge in distributed ontologies to reduce confusability and ambiguity and to provide a reliable semantic confidence measure through a new concept of ontological distance. This concept is also incorporated into the dialogue manager component. These innovative solutions are expected to provide ubiquitous and intuitive access to the enterprise information systems by using speech/RFID modality, which will ultimately lead to important technological advances in real-life RFID applications of the manufacturing industry.

探索新的研究途径，以便通过使用语音模式和射频识别（RFID）技术提供可靠的人与物体交互。其目的是将语音技术集成到 RFID 网络中，使操作员能够与 RFID 设备、RFID 标签物体和相关信息系统进行口头通信。 语音和 RFID 技术的结合有望提高众多制造和业务运营（例如物品跟踪和监控、仓库管理和运输）的速度、准确性、人体工程学和安全性。然而，与语音组件的可靠性相关的许多问题仍未解决，并构成了语音RFID系统部署的障碍。为了确保所提出的 RFID 语音框架在现实生活条件（工厂和仓库环境）中的有效性，应提供非常强大的实时语音识别和无约束且灵活的对话方案。因此，我们提出的策略包括在声学和语言层面上进行操作。在声学层面，提出了基于仿生方法（鸟类聚集和遗传算法）的尖端算法来优化非平稳噪声的估计和跟踪。在语言层面，所提出的策略包括利用分布式本体中的知识来减少混淆性和歧义性，并通过本体距离的新概念提供可靠的语义置信度度量。这个概念也被纳入对话管理器组件中。这些创新解决方案预计将通过语音/RFID 模式提供对企业信息系统的普遍且直观的访问，最终将在制造业的现实 RFID 应用中带来重要的技术进步。