tailieunhanh - Advances in Human Robot Interaction Part 13

Tham khảo tài liệu 'advances in human robot interaction part 13', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Learning to Understand Expressions of Approval and Disapproval through Game-Based Training Tasks 289 Kayikci et al. Kayikci et al. 2007 utilized Hidden Markov Models and a neural associative memory for learning to understand short speech commands in a three-staged recognition procedure. First the system recognized a speech signal as a sequence of diphones or triphones. In the next step the sequences were translated into words using a neural associative memory. The last step employed a neural associative memory to finally obtain a semantic representation of the utterance. In the same way as the approaches outlined above our learning algorithm attempts at assigning a meaning to an observed auditory or visual pattern using HMMs as a basis. However our system is not trying to learn the meaning of individual words or symbols but focuses on learning patterns expressing a feedback as a whole. Moreover our proposed approach is not limited to a single modality but tries to integrate observations from different modalities. For learning associations between approval or disapproval and the HMM representations of the observed user behavior classical conditioning is used in our system. Mathematical theories of classical conditioning were extensively researched upon in the field of cognitive psychology. An overview can be found in Balkenius Moren 1998 . The relation of classical conditioning to the phase of learning word meanings in human speech acquisition has been postulated in the book Verbal Behavior by B. F. Skinner Skinner 1957 and has been adopted and modified by researchers in the field of behavior analysis. An explanation of the processes involved in learning word meanings by conditioning is described by B. Lowenkron in Lowenkron 2000 . There have been different approaches to use classical conditioning for teaching a robot such as in Balkenius 1999 . However to our knowledge our proposed approach is the first one to apply classical conditioning to acquire an .