B.TECH( IT 3rd year) [2010-2014]

Yatin Goel [ 05810403110 ] Pratik Kumar [ 04510403110 ]Gaurav Bansal [ 01210403110 ]Amit Chanana [ 00510407711 ]

Project Title Real Time Voice Translator

Objectives

The purpose of this project is to develop a Voice Application that was able to do a real time translation from a spoken sentence in one language to a spoken sentence in other language. The basic idea is to enable that two people, who are talking through a voice call in two different countries, were able to understand each other speaking different languages due to an automatic real time translation done by a machine.

Motivation

Today, speech translation systems are being used throughout the world. Examples include medical facilities, schools, police, hotels, retail stores, and factories. These systems are applicable anywhere that spoken language is being used to communicate.

About the project

Speech Translation is the process by which conversational spoken phrases are instantly translated and spoken aloud in a second language. This differs from phrase translation, which is where the system only translates a fixed and finite set of phrases that have been manually entered into the system. Speech translation technology enables speakers of different languages to communicate. It thus is of tremendous value for humankind in terms of science, cross-cultural exchange and global business

A speech translation system would typically integrate the following three software technologies: automatic speech recognition (ASR), machine translation (MT) and voice synthesis (TTS).

The speaker of language A speaks into a microphone and the speech recognition module recognizes the utterance. It compares the input with a phonological model, consisting of a large corpus of speech data from multiple speakers. The input is then converted into a string of words, using dictionary and grammar of language A, based on a massive corpus of text in language A.

The machine translation module then translates this string. Early systems replaced every word with a corresponding word in language B. Current systems do not use word-for-word translation, but rather take into account the entire context of the input to generate the appropriate translation. The generated translation utterance is sent to the speech synthesis module, which estimates the pronunciation and intonation matching the string of words based on a corpus of speech data in language B. Waveforms matching the text are selected from this database and the speech synthesis connects and outputs them.

Platform to be used Software Requirement :- Java/Python ,etc.

Hardware Requirements :- 2 computer System , 2 Android Device

System Req. :- windows 7 / xp

Memory :- 2 Gb

Hard Disk :- 320 Gb

Processor :- Intel core i5

Referenceswww.microsoft.com

www.wikipedia.comwww.translation.paralink.com

www.traducegratis.com

www.translator.dictionary.com/text.html

www.freetranslation.com

www.translate.google.com/translate_t?hl=en

www.babelfish.yahoo.com