Command Recognition through keyword analysis

• Main Author: Sutherland, Alexander
• Format: Others
• Language: English
• Published: Umeå universitet, Institutionen för datavetenskap 2014
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-92840

Many modern day speech recognition systems are rendered ineffective by the environments they reside in. These environments are often loud and busy forcing spoken words to contend with background noise. It is often the case that a system will be forced to function with highly fragmented and incomplete data. This leads to a need for a system capable of functioning without having access to an entire sentence but only a limited set of words. A system that is required to be capable of understanding natural language and phrases as users cannot be expected to have prior knowledge of how to interact with the system. The focus of this thesis is to attempt to create a system capable of binding keywords to actions using Association Rules as a basis. Association Rules allow the system to choose its own keywords allowing a higher level of flexibility and a possibility for self learning and improvement. A very basic AR-based system has been designed and implemented which will allow for testing of potential accuracy. After having read through the thesis the reader should have a working knowledge of how an association rule based recognition system functions, an idea of system precision and be familiar with the advantages and disadvantages of such a system. This thesis should provide a more than adequate basis for future implementations of such a system whether they be scholastic or commercial. Results show that the system has potential but association rules on their own are not enough to allow the system to function independently without taking into concern the nature of the data and implementation.