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In this degree project we present a way to construct a synchronization system that is able to create a timings file, which is the file the system uses to know how to sync the eBook and audiobook, using speech recognition and estimation algorithms. This file is then used by the system to let the user select a sentence and have the audiobook start reading from that sentence, or vice versa. This system can create these files with a mean offset from a manu-ally timed file which is within our expectations for the system. We use estimation algorithms to fill in the blanks where the speech recognition falls short. Speech recognition accuracy is typically between 40-60%, sometimes dipping lower, so there are blanks to fill in. Using basic algebraic principles of calculating velocity we can ex-trapolate the speed of a reader, using the duration of the audiobook as the time and the amount of characters written as the distance. For increased accuracy we derive this value on a per-chapter basis. Using this method we are able to create accurate files, which the user can use to freely sync any location in the book. Our system is designed to work for any book in the world that does not have an audiobook which cuts off between sentences in the audio files. We manually create timings files for four different books with widely varying publishing dates, author styles, reader style and gender to create as wide and representative a testing pool as possible for the project

Playing has been part of people's lives since the beginning of time. However, play does not take place in silence (isolated from speech and sound). The games people play allow them to interact and to learn through experiences. Speech often forms an integral part of playing games. Video games also allow players to interact with a virtual world and learn through those experiences. Speech input has previously been explored as a way of interacting with a game, as talking is a natural way of communicating. By talking to a game, the experiences created during gameplay become more valuable, which in turn facilitates effective learning. In order to enable a game to “hear", some issues need to be considered. A game, that will serve as a platform for speech input, has to be developed. If the game will contain learning elements, expert knowledge regarding the learning content needs to be obtained. The game needs to communicate with a speech recognition system, which will recognise players' speech inputs. To understand the role of speech recognition in a game, players need to be tested while playing the game. The players' experiences and opinions can then be fed back into the development of speech recognition in educational games. This process was followed with six Financial Management students on the NWU Vaal Triangle campus. The students played FinMan, a game which teaches the fundamental concepts of the “Time value of money" principle. They played the game with the keyboard and mouse, as well as via speech commands. The students shared their experiences through a focus group discussion and by completing a questionnaire. Quantitative data was collected to back the students' experiences. The results show that, although the recognition accuracies and response times are important issues, speech recognition can play an essential part in educational games. By freeing learners to focus on the game content, speech recognition can make games more accessible and engaging, and consequently lead to more effective learning experiences. / MSc (Computer Science), North-West University, Vaal Triangle Campus, 2014

Neural networks have recently been applied to real-world speech recognition problems with a great deal of success. This thesis developes a strategy for optimising a neural network known as the Radial Basis Function classifier (RBF), on a large spoken letter recognition problem designed by British Telecom Research Laboratories. The strategy developed can be viewed as a compromise between a fully adaptive approach involving prohibitively large amounts of computation, and a heuristic approach resulting in poor generalisation. A value for the optimal number of kernel functions is suggested, and methods for determining the positions of the centres and the values of the width parameters are provided. During the evolution of the optimisation strategy it was demonstrated that spatial organisation of the centres does not adversely affect the ability of the classifier to generalise. An RBF employing the optimisation strategy achieved a lower error rate than a multilayer perceptron and two traditional static pattern classifiers on the same problem. The error rate of the RBF was very close to the theoretical minimum error rate obtainable with an optimal Bayes classifier. In addition to error rate, the performance of the classifiers was assessed in terms of the computational requirements of training and classification, illustrating the significant trade-off between computational investment in training and level of generalisation achieved. The error rate of the RBF was compared with that of a well established method of dynamic classification to examine whether non-linear time normalisation of word patterns was advantageous to generalisation. It was demonstrated that the dynamic classifier was better suited to small-scale speech recognition problems, and the RBF to speaker-independent speech recognition problems. The dynamic classifier was then combined with a neural network algorithm, greatly reducing its computational requirement without significantly increasing its error rate. This system was then extended into a novel system for visual feedback therapy in which speech is visualised as a moving trajectory on a computer screen.

Thesis (MEng(TelecommunicationsbyResearch))--University of South Australia, 2003.

Thesis (M.S.)--Rochester Institute of Technology, 1989. / Includes bibliographical references (leaves 20-21).

Thesis (M.S.)--Ohio University, June, 2001. / Title from PDF t.p.

Thesis (M.S.)--Rochester Institute of Technology, 1989. / Includes bibliographical references (leaves 81-85).

Thesis (M.S.)--Rochester Institute of Technology, 1989. / Includes bibliographical references (leaves 73-75).