Machine Translation Approaches and Survey for Indian Languages
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paper_title: METIS-II: Example-based machine translation using monolingual corpora - System description

paper_content:

The METIS-II project1 is an example-based machine translation system, making use of minimal resources and tools for both source and target language, making use of a target-language (TL) corpus, but not of any parallel corpora. In the current paper, we discuss the view of our team on the general philosophy and outline of the METIS-II system.
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paper_title: Statistical Post-Editing on SYSTRAN's Rule-Based Translation System

paper_content:

This article describes the combination of a SYSTRAN system with a "statistical post-editing" (SPE) system. We document qualitative analysis on two experiments performed in the shared task of the ACL 2007 Workshop on Statistical Machine Translation. Comparative results and more integrated "hybrid" techniques are discussed.
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paper_title: Hybrid Example-Based SMT: The Best Of Both Worlds?

paper_content:

(Way and Gough, 2005) provide an in-depth comparison of their Example-Based Machine Translation (EBMT) system with a Statistical Machine Translation (SMT) system constructed from freely available tools. According to a wide variety of automatic evaluation metrics, they demonstrated that their EBMT system outperformed the SMT system by a factor of two to one. ::: ::: Nevertheless, they did not test their EBMT system against a phrase-based SMT system. Obtaining their training and test data for English--French, we carry out a number of experiments using the Pharaoh SMT Decoder. While better results are seen when Pharaoh is seeded with Giza++ word- and phrase-based data compared to EBMT sub-sentential alignments, in general better results are obtained when combinations of this 'hybrid' data is used to construct the translation and probability models. While for the most part the EBMT system of (Gough & Way, 2004b) outperforms any flavour of the phrase-based SMT systems constructed in our experiments, combining the data sets automatically induced by both Giza++ and their EBMT system leads to a hybrid system which improves on the EBMT system per se for French--English.
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paper_title: Rule-Based Translation with Statistical Phrase-Based Post-Editing

paper_content:

This article describes a machine translation system based on an automatic post-editing strategy: initially translate the input text into the target-language using a rule-based MT system, then automatically post-edit the output using a statistical phrase-based system. An implementation of this approach based on the SYSTRAN and PORTAGE MT systems was used in the shared task of the Second Workshop on Statistical Machine Translation. Experimental results on the test data of the previous campaign are presented.
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paper_title: ANGLABHARTI: a multilingual machine aided translation project on translation from English to Indian languages

paper_content:

An English to Indian languages machine aided translation system, named ANGLABHARTI, has been developed. It uses pattern directed approach using context free grammar like structures. A 'pseudo-target' is generated which is applicable to a group of Indian languages. Set of rules are acquired through corpus analysis to identify the plausible constituents with respect to which movement rules for the 'pseudo-target' are constructed. A number of semantic tags are used to resolve sense ambiguity in the source language. Alternative meanings for the unresolved ambiguities are retained in the pseudo target language code. A text generator module for each of the target languages transforms the pseudo target language to the target language. A corrector for ill-formed sentences is used for each of the target languages. Finally, a human-engineered post-editing package is used to make the final corrections. The post-editor needs to know only the target language. The strategy used in ANGLABHARTI lies in between the transfer and the interlingua approach. It is better than the transfer approach, as the translation is valid for a host of target language sentences, but falls short of genuine interlingua, in the sense that it ignores complete disambiguation/understanding of the text to be translated.
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paper_title: ANGLABHARTI: a multilingual machine aided translation project on translation from English to Indian languages

paper_content:

An English to Indian languages machine aided translation system, named ANGLABHARTI, has been developed. It uses pattern directed approach using context free grammar like structures. A 'pseudo-target' is generated which is applicable to a group of Indian languages. Set of rules are acquired through corpus analysis to identify the plausible constituents with respect to which movement rules for the 'pseudo-target' are constructed. A number of semantic tags are used to resolve sense ambiguity in the source language. Alternative meanings for the unresolved ambiguities are retained in the pseudo target language code. A text generator module for each of the target languages transforms the pseudo target language to the target language. A corrector for ill-formed sentences is used for each of the target languages. Finally, a human-engineered post-editing package is used to make the final corrections. The post-editor needs to know only the target language. The strategy used in ANGLABHARTI lies in between the transfer and the interlingua approach. It is better than the transfer approach, as the translation is valid for a host of target language sentences, but falls short of genuine interlingua, in the sense that it ignores complete disambiguation/understanding of the text to be translated.
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paper_title: Anusaaraka: Machine Translation in Stages

paper_content:

Fully-automatic general-purpose high-quality machine translation systems (FGH-MT) are extremely difficult to build. In fact, there is no system in the world for any pair of languages which qualifies to be called FGH-MT. The reasons are not far to seek. Translation is a creative process which involves interpretation of the given text by the translator. Translation would also vary depending on the audience and the purpose for which it is meant. This would explain the difficulty of building a machine translation system. Since, the machine is not capable of interpreting a general text with sufficient accuracy automatically at present - let alone re-expressing it for a given audience, it fails to perform as FGH-MT. FOOTNOTE{The major difficulty that the machine faces in interpreting a given text is the lack of general world knowledge or common sense knowledge.}
---
paper_title: Anusaaraka: Machine Translation in Stages

paper_content:

Fully-automatic general-purpose high-quality machine translation systems (FGH-MT) are extremely difficult to build. In fact, there is no system in the world for any pair of languages which qualifies to be called FGH-MT. The reasons are not far to seek. Translation is a creative process which involves interpretation of the given text by the translator. Translation would also vary depending on the audience and the purpose for which it is meant. This would explain the difficulty of building a machine translation system. Since, the machine is not capable of interpreting a general text with sufficient accuracy automatically at present - let alone re-expressing it for a given audience, it fails to perform as FGH-MT. FOOTNOTE{The major difficulty that the machine faces in interpreting a given text is the lack of general world knowledge or common sense knowledge.}
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paper_title: Evaluation of Hindi to Punjabi Machine Translation System

paper_content:

Machine Translation in India is relatively young. The earliest efforts date from the late 80s and early 90s. The success of every system is judged from its evaluation experimental results. Number of machine translation systems has been started for development but to the best of author knowledge, no high quality system has been completed which can be used in real applications. Recently, Punjabi University, Patiala, India has developed Punjabi to Hindi Machine translation system with high accuracy of about 92%. Both the systems i.e. system under question and developed system are between same closely related languages. Thus, this paper presents the evaluation results of Hindi to Punjabi machine translation system. It makes sense to use same evaluation criteria as that of Punjabi to Hindi Punjabi Machine Translation System. After evaluation, the accuracy of the system is found to be about 95%.
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paper_title: Phrase based English – Tamil Translation System by Concept Labeling using Translation Memory

paper_content:

this paper, we present a novel framework for phrase based translation system using translation memory by concept labeling. The concepts are labeled on the input text, followed by the conversion of text into phrases. The phrase is searched throughout the translation memory, where the parallel corpus is stored. The translation memory displays all source and target phrases, wherever the input phrase is present in them. Target phrase corresponding to the output source phrase having the same concept as that of input source phrase, is chosen as the best translated phrase. The system is implemented for English to Tamil translation.
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paper_title: Phrase based English – Tamil Translation System by Concept Labeling using Translation Memory

paper_content:

this paper, we present a novel framework for phrase based translation system using translation memory by concept labeling. The concepts are labeled on the input text, followed by the conversion of text into phrases. The phrase is searched throughout the translation memory, where the parallel corpus is stored. The translation memory displays all source and target phrases, wherever the input phrase is present in them. Target phrase corresponding to the output source phrase having the same concept as that of input source phrase, is chosen as the best translated phrase. The system is implemented for English to Tamil translation.
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paper_title: Rule based Sentence Simplification for English to Tamil Machine Translation System

paper_content:

Machine translation is the process by which computer software is used to translate a text from one natural language to another but handling complex sentences by any machine translation system is generally considered to be difficult. In order to boost the translation quality of the machine translation system, simplifying an input sentence becomes mandatory. Many approaches are available for simplifying the complex sentences. In this paper, Rule based technique is proposed to simplify the complex sentences based on connectives like relative pronouns, coordinating and subordinating conjunction. Sentence simplification is expressed as the list of sub-sentences that are portions of the original sentence. The meaning of the simplified sentence remains unaltered. Characters such as („.‟,‟?‟) are used as delimiters. One of the important pre-requisite is the presence of delimiter in the given sentence. Initial splitting is based on delimiters and then the simplification is based on connectives. This method is useful as a preprocessing tool for machine translation.
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Title: Machine Translation Approaches and Survey for Indian Languages

Section 1: Introduction
Description 1: Introduce the concept of Machine Translation (MT), its importance, and challenges, especially in the context of Indian languages.

Section 2: History of MT
Description 2: Provide a historical overview of the development of MT systems, including key milestones and technologies.

Section 3: MT Approaches
Description 3: Discuss the various methodologies employed in MT, including rule-based, statistical-based, hybrid-based, example-based, knowledge-based, principle-based, and online interactive systems.

Section 4: Rule-based Approach
Description 4: Explain the rule-based MT approach and its different categories: Direct Translation, Interlingua Based Translation, and Transfer-Based Translation.

Section 5: Statistical-based Approach
Description 5: Dive into the statistical-based MT approaches, including Word Based Translation, Phrase Based Translation, and Hierarchical Phrase Based Model.

Section 6: Hybrid-based Translation
Description 6: Describe the hybrid approach that combines statistical and rule-based methodologies for MT.

Section 7: Example-based Translation
Description 7: Elaborate on the example-based MT approach that uses analogical reasoning and bilingual corpora for translation.

Section 8: Knowledge-Based MT
Description 8: Discuss the knowledge-based MT approach that relies on deep linguistic and world knowledge for translation.

Section 9: Principle-Based MT
Description 9: Describe the principle-based MT approach derived from Chomsky's Generative Grammar principles.

Section 10: Online Interactive Systems
Description 10: Explain how user interaction is integrated into MT systems to improve translation accuracy.

Section 11: Major MT Developments in India: A Literature Survey
Description 11: Provide a detailed survey of the major MT systems developed in India, including their methodologies, language pairs, and current status.