Search

The www is a dynamic environment and it is difficult to capture the user preferences and interests without interfering with the normal activity of the user. Hence to improve user searching in the World Wide Web, we have proposed a personalized search system that supports user searches by learning about user preferences and by observing responses to prior search experiences aided by a new index called the User Conceptual Index (UCI). This paper models every user's search behavior as a User's Search Behavior (USB) Graph. The main focus of this paper is the analysis of the USB graph and the redesign of the UCI using the results arrived from the analysis. [ABSTRACT FROM AUTHOR]

The goal of this paper is to provide a visual structure to view the temporal and thematic content of English news documents. This paper combines both information extraction techniques and visualization techniques to visualize the documents content. Topical information present in the documents are extracted by applying Booksteins model and by calculating the various measures associated with the model. Temporal information is extracted as date information from the documents. Later the extracted information is converted into a signal and both discrete and continuous wavelet transfor-mations are applied over the signal. The content of the document is visualized at varying levels of detail by multi resolution analysis techniques available in wavelets. This gives a wavelet based visualization model which enables us to view the spread of topics across a document, the portions of the document that are most involved in topic description, and the contribution of documents in the corpus from the temporal perspective. [ABSTRACT FROM AUTHOR]

This paper describes the improvement of the quality of Tamil text to speech using LPC based diphone database and the modification of syllable pitch through time scale modification. Speech is generated by concatenative speech synthesizer. Syllable units need to be concatenated such that spectral discontinuities are lowered at unit boundaries without degrading their quality. Smoothing is done by inserting suitable diphone at the concatenation boundary and changing the syllable pitch by performing time scale modification. The suitable diphone is chosen based on LPC coefficient files and their corresponding residuals. [ABSTRACT FROM AUTHOR]

This paper presents a neural network approach for speech recognition in Tamil language. In the present work the structure of a speaker-independent system for isolated word recognition, based on a neural network paradigm combined with a dynamic programming algorithm is applied. The experimental results demonstrate that a hybrid model leads to higher recognition rates than the classic technologies. [ABSTRACT FROM AUTHOR]

An essential element of any speech recognition system is the language model. A language model attempts to identify and make use of the regularities in natural language to better define language syntax for easier recognition. One major obstacle in speech recognition is the variability and uncertainty of message content. This coupled with inherent noise distortion and losses that occur in speech emphasize the need for a good language model. This paper describes the work done in generation of language model for Tamil speech recognition system. From the study the performance of Morpheme based Language model is better compared to other models tried for Tamil speech recognizer. [ABSTRACT FROM AUTHOR]