72.1 percent of the consumers spend most or

all of theirtime on sites in their own

language

72.4 percent say they would be more likely to buy a product with information

in their own language

56.2 percent say that the ability to obtain

information in their own language is more

important than price.

Real-time communications where it would not be practical for a human to translate (e.g. chat and email.)

Content that does not need to be perfect but just approximately understandable (e.g. any website for a quick review.)

Content that would normally be too expensive or too slow to translate with a human only translation approach (e.g. many projects that have insufficient budget for a human only approach.)

High value content that is changing every hour and every day there is time sensitivity (e.g. stock market news.)

AFTER 1 HOUR AFTER 2 HOUR

RULE BASED MACHINE TRANSLATION(RBMT)

STATISTICAL MACHINE TRANSLATION(SMT)

• Rules-based systems use a combination of language and grammar rules plus dictionaries for common words. Specialist dictionaries are created to focus on certain industries or disciplines.

RULE BASED APPROACH

GRAMMAR RULE

LEXICONSOFTWARE PROGRAM

RBMT

Direct MTTransfer Based

MTInterlingua

• Method based on Dictionary entries, which means that the words will be translated as a dictionary does – word by word, usually without much correlation of meaning between them followed by some syntactic arrangement.

• Dictionary lookups may be done with or without morphological analysis(Structure of word).

• Direct - based machine translation is ideally suitable for the translation of long lists of phrases.

SL-TL Dictionary

SL TEXT TL TEXT

SL TEXT ANALYSIS TRANSFER GENERATION TL TEXT

SLDICTIONARY / GRAMMAR

SL-TL DICTIONARY/GRAMMAR

TL GRAMMAR/DICTIONARY

• In this translation system, a database of translation rules is used to translate text from source to target language. Whenever a sentence matches one of the rules, or examples , it is translated directly using a dictionary.

• A transfer-based approach first converts the source language into an internal representation (IR) which is dependent on the source but not the Target language. The system then transform IRs into a form IRt which is independent of the source language and depends only on the Target lagunage and finally generates the target language output from IRt

Lexical Level

Syntactic Level

Semantic Level

Intermediate Representation

Based On Source Language

Intermediate Representation Based On Target

Language

ANALYSIS

TRANSFER

GENERATION

सीता बाग में सोयि

ANALYSIS

• The Interlingual approach converts the input into a single internal representation(IR) That is independent of both source and target languages,and then converts from this into the output.

AnalysisInterlingua

Representation GenerationSL TEXT TL TEXT

• The advantage in multilingual machine translations is that no transfer component has to be created for each language pair

• The obvious disadvantage is that the definition of an interlingua is difficult and maybe even impossible for a wider domain.

STATISTICAL MACHINE TRANSLATION• Statistical machine translation (SMT) learns how

to translate by analyzing existing human translations (known as bilingual text corpora).

• Machine translator can use a database as the source for all the information it need for translating.

ISSUES IN MACHINE TRANSLATION• Word orderWord order in languages differs. Some classification can be done bynaming the typical order of subject (S), verb (V) and object (O) in asentence . Some languages have word orders as SOV. The targetlanguage may have a different word order. In such cases, word to wordtranslation is difficult. For example, English language has SVO and Hindilanguage has SOV sentence structure.

• Ambiguity

A given word or sentence can have more than onemeaning.For ex, the word ‘’party’’ could mean apolytical party, or a social event,and deciding thesuitable one in perticular case is crucial to getting rightanalysis and therefore right translation

• The third reason is that when human use naturallanguage, they use an enormous amount of commonsense, and knowledge about the world, which helpsto resolve the ambiguity. For ex. in ‘’He went to thebank, but it was closed for lunch’’,we can infer that‘bank’ refers to a financial institution, and not a riverbank, because we know from our knowledge of theworld that only the former type of bank can beclosed for lunch.

SYSTRAN TRANSLATOR

• RULE BASED MACHINE TRANSLATION SYSTEM.

• SUPPORT 45 LANGUGAES.

BING TRANSLATOR

• STATISTICAL BASED MACHINE TRANSLATION.

• SUPPORT 47 LANGUGAES.

GOOGLE TRANSLATOR

• STATISTICAL BASED MACHINE TRANSLATION

• SUPPORT 80 LANGUAGES.

EXISTING MACHINE TRANSLATION