Automatic Speech Recognition using Dynamic Bayesian Networks
نویسندگان
چکیده
New ideas to improve automatic speech recognition have been proposed that make use of context user information such as gender, age and dialect. To incorporate this information into a speech recognition system a new framework is being developed at the mmi department of the ewi faculty at the Delft University of Technology. This toolkit is called Gaia and makes use of Dynamic Bayesian networks. In this thesis a basic speech recognition system was built using Gaia to test if speech recognition is possible using Gaia and dbns. dbn models were designed for the acoustic model, language model and training part of the speech recognizer. Experiments using a small data set proved that speech recognition is possible using Gaia. Other results showed that training using Gaia is not working yet. This issue needs to be addressed in the future and also the speed of the toolkit.
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