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Power consuming users and buildings with different power consumption patterns may be treated with different conditions and can be taken into consideration with different parameters during capacity planning and distribution. Thus the automated, unsupervised categorization of power consumers is a very important task of smart power transmission systems. Knowing the behavioral categories of power consumers...
This paper presents our work on developing acoustic models using deep neural networks (DNN) for low resource languages. This is considered one of the challenging problems in automatic speech recognition (ASR) as DNNs need large amount of data for building efficient models. The techniques explored in this approach use a common idea of transferring knowledge from models of high resource language to...
We applied genetic programming algorithm to learn the behavior of an occupant in single person office based on motion sensor data. The learned rules predict the presence and absence of the occupant with 80%-83% accuracy on testing data from 5 different offices. The rules indicate that the following variables may influence occupancy behavior: 1) the day of week, 2) the time of day, 3) the length of...
This paper establishes a speaker-independent pronunciation recognition and assessment system with 673 words for mandarin Chinese under the background of a Chinese learning system framework. The recognition part is based on HTK using HMM (Hidden Markov Models) and improved in the aspect of acoustic model. Making use of the recognition results and the log-likelihood obtained from the Viterbi coding,...
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