Sharif Digital Repository

In this thesis we describe Keyword Spotting in continuous speech based on hidden Markov modeling. The aim of keyword spotting is to detect the specified keywords and get rid of other speech streams by a network of keyword models and a garbage model. Phoneme recognition is the basis of this work and we obtain appropriate feature vector and model for phonemes. Two main parts of keyword spotting are the keyword models and the filler model connected together by a network grammar. The Viterbi algorithm can recognize keywords and non-keywords using the network grammar. Each keyword model is created by concatenation of phoneme HMMs. In experiments keyword models with one skip in states of HMMs... 

Human Activity Recognition (HAR) has had tremendous improvements in the field of elderly monitoring and telerehabilitation. An anchor point for HAR systems in telerehabilitation is supervising rehabilitative excercises. For Parkinson’s disease (PD) patients, a group of rehabilitative activities, known as Lee Silverman Voice Treatment-BIG, or LSVT-BIG, have shown to be effective in improving motor performance. Similar to any rehabilitative measure, delivering these activities requires the supervision of an expert or clinician, so that the patient receives proper feedbacks. HAR systems can replace human experts. They can recognize activities and provide the user with proper feedback. HAR...