Grant: Discovery Grants Program - Individual
Université de Moncton
$29,000.00
Human-to-Object Interaction by Integrating Speech Technology into Radio Frequency Identification Networks
FY 2013-14
Summary
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.
Program
Discovery Grants Program - Individual
Recipient
Location
New Brunswick, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
283139-2013
Name nom
Selouani, SidAhmed
Department département
Campus de Shippagan
Organization id
73
Institution établissement
Université de Moncton
Province en
New Brunswick
Province fr
Nouveau-Brunswick
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2013
Competition year année de concours
2013
Award amount
29000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2514
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Digital signal processing
Research subject fr
Traitement des signaux numériques
Partie
1
Nb partie
5
Application title
Human-to-Object Interaction by Integrating Speech Technology into Radio Frequency Identification Networks
Keyword
NSERC
Application summary
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.