Utkal University We Work On Image Processing Speech Processing Knowledge Management

Image Processing (A) Optical Character Recognition (OCR):  Converts scanned Oriya content to text  An OCR with TTS - DIVYADRUSTI  User - Press, Media & Educational Institutes  Operates in command mode so useful for Illiterate and Visually Challenged.  Got IPR & Tested by SQTC, ETDC Banglore. (B) English Reader System  Uses English OCR System  Integrated with Microsoft Text To Speech Engine  And Speech To Text Engine to operate in command mode.

Speech Processing (A) Text To Speech (TTS) System:  Speech synthesizer for Oriya language is designed by the character based concatenation technique.  The transition between two characters is stored by taking the help of Paninian philology to give a natural shape to the output.  In addition to Oriya language we are in the process of developing a TTS system for Hindi in syllable base concatenation  Got IPR & Tested by SQTC, ETDC Banglore (B) Speech To Text (STT) system:  Recognising words, designed through a training process of phones, diphones and triphones.  Telephone Directory system based on Oriya character recognition system.  Applied for IPR.

Knowledge Management Machine Translation Normal sentences with WSD Lexical Resources (A)e-Dictionary (Oriya  English  Hindi) – Got IPR. and Tested by SQTC, ETDC Banglore 27,000 Oriya, 30,000 English and 20,000 Hindi words. (B) Oriya WordNet with Morphological Analyzer. Got IPR., Tested by SQTC, ETDC, Banglore -1,000 Lexicon. (C) Ori-Spell (Oriya Spell Checker) Got IPR, Tested by SQTC, ETDC Banglore, 1,70,000 words (root and derived). (D) Trilingual Word Processor (Hindi- English-Oriya) Integrated with Spell Checker and Grammar Checker.

San-Net(Sanskrit Word-Net) Developed using Navya-NyAya()Philosophy and Paninian Grammar Beside Synonym, Antonym, Hypernym, Hyponym, Holonym and Meronyms etc., some more relation such as: Analogy, Etymology, Definition, Nominal Verb, Nominal Qualifier, Verbal Qualifier and Verbal Noun have been introduced in San-Net. San-Net can be used for Indian language understanding, translating, summarizing and generating. A standard Knowledge Base (KB) has been developed for analyzing syntactic, semantic and pragmatic aspects of any lexicon. KM(Sanskrit)

Present Interest Hand Written Recognition of old scripts using Neural Network OCR for Brhami Script Automatic Speech Recognition System Speaker Recognition and Accent Analysis using HMM TTS for other languages (Indian) to make Reader System Sanskrit WordNet based Machine Translation System Morphological Analyser for Sanskrit Navya Nyaya Philosophy to be extensively used for it. Help to have better WSD as NNP provides a effective Conceptual analysisng capability.

Thank you