58 Mukesh Yadav, Gayatri Hegde International Journal of Innovations & Advancement in Computer Science IJIACS ISSN 2347 – 8616 Volume 3, Issue 10 December 2014 Voice Translation on Windows & Linux machine Mukesh Yadav Computer Engg. Department PIIT, New Panvel India Gayatri Hegde Computer Engg. Department PIIT, New Panvel India ABSTRACT Voice translation tools provide services to convert words to target language using natural language processing. There are parsing methods which concentrate on capturing keywords & translating them to target language. Current techniques to optimize processing time are template matching, indexing the frequently used words using probability search and session- based cache. In this paper, we are proposing a model which optimize processing time and increasing the throughput of voice translation services using these techniques and developing a project to translate one language to another. The languages used are Hindi and English. The input taken is user voice in any one language. Keywords Sphinx, Text-to-speech, Natural Language Processing, voice translation, speech recognition, speech synthesis, template matching, probability search, session-based cache. INTRODUCTION Language is a means of communication between two individuals with the use of words and sentences understood recollected and reciprocated in the same format by the other individual. Language is a basic form of written or speech communication. Especially, in a nation like India where the language and dialect changes with region. So we need a translation layer that can eliminate the linguistic barrier. Improvements in existing system include recognition rate which is expressed by word or by sentence, system accommodating time for new speakers, dependence or independence on the speaker, dimension of recognizable vocabulary, decision and recognition time. The methods and algorithms till now are discriminant analysis methods based on Bayesian discrimination, Hidden Markov Models & Dynamic Programming – Dynamic Time algorithm (DTW) & Neural Networks. Alternative of dynamic programming DTW algorithm implementation in speech recognition is also referred in development of this project. In this paper, we propose a model for voice translation on laptop or personal computer systems. This model is implemented on windows operating system and linux operating system. PROBLEM STATEMENT During communication it is essential to recognize a language correctly. Since many times recognition is not just the goal, the result of recognition is an intermediate of the system. The result is further used as input for another module. Therefore if the task of recognition is not correct then modules which rely on the result of recognition may not perform the further operation correctly or may produce partially correct result. PROPOSED MODEL In the proposed system the user voice is taken as the input using microphone in the windows machine, it is analyzed by the speech recognizer in which acoustic signals captured by the micro phone are converted to a set of meaningful words. When speech is produced in a sequence of words, language models or artificial grammars are used to restrict the combination of words. After that words obtained are parsed in Natural Language Parsing model. Then information is extracted from the open source library. Then the input text is matched with database text. Then the output text is converted to voice and sent to speech synthesizer and output voice is heard by the user. Fig 1: Architecture diagram for voice translation Speech Recognizer NLU Parsing Model Information Extractor Statistical Language Generation Phrase/Word Translator Speech Synthesizer Semantics Source Speech Target Speech