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.

探索了新的研究途径，以通过使用语音方式和射频识别（RFID）技术提供可靠的人对观察互动。目的是将语音技术集成到RFID网络中，以允许人类操作员与RFID设备，RFID标记的对象和相关信息系统进行口头通信。 言语和RFID技术的结合有望提高众多制造和业务运营的速度，准确性，人体工程学和安全性，例如项目跟踪和监视，仓库管理以及运输。但是，许多与语音组件的可靠性相关的问题仍未解决，并在部署启用语音的RFID系统的方式构成了障碍。为了确保拟议的RFID语音框架在现实生活条件（制造业和仓库环境）中的功效，应提供非常健壮的实时语音识别以及不受限制且灵活的对话方案。因此，我们提出的策略包括在声学和语言水平上运作。在声学水平上，提出了基于生物启发的方法（鸟卵和遗传算法）的尖端算法，以优化非平稳噪声的估计和跟踪。在语言层面上，拟议的策略包括利用分布式本体论中的知识来减少混淆性和歧义性，并通过新的本体论距离概念提供可靠的语义置信度度量。此概念还将其纳入对话管理器组件中。预计这些创新的解决方案将通过使用语音/RFID模式为企业信息系统提供无处不在的直观访问，这最终将导致制造业现实生活中RFID应用的重要技术进步。