Generation of Bilingual Dictionaries using Comparable and Quasi Comparable Corpora

The amount of information available on the web is increasing rapidly. The number of internet users is also increasing every day. A significant section of internet users is monolingual. They want to express themselves in their native language and also seeking information in the same. Hence, multilingual content over the internet is also increasing at a rapid pace. There is a need of systems which empowers such internet users to let them express themselves in the language of their choice and can provide them answers to information requests irrespective of the language barrier. Cross-lingual term associations are very important for many interlingual applications. Machine Translation system is a sub-field of computational linguistics which aims at translating text from one language to other. All MT systems at the core depend on bilingual dictionaries. The bilingual dictionaries are important resources for such NLP applications as statistical machine translation and cross-language information extraction systems. The bilingual dictionary is one such important resource where entries are word translations. They also can serve to enhance existing dictionaries, for second language teaching and learning. Manually created resources are usually more accurate and do not contain noisy information, in contrast, to automatically learned dictionaries. Scientific community seeks for the methods to achieve similar accuracy level and broader terminology scope by automatic means. In this thesis, we try to address the problem of generating bilingual dictionaries automatically. We propose two different approaches to generating bilingual dictionaries for English-Hindi pair. Both the approaches proposed in this thesis are language independent and hence can be used to build dictionaries for other language pairs which are phonetically rich. Hindi is very under-represented on the web because of many technical and socio-cultural reasons. Many languages, like Hindi, suffer from the limited availability of the language resources/tools. It is crucial to develop a language-independent approach for such languages. In this thesis, though we have shown our experiments for English and Hindi language pair, our approach can be easily extendable to other language pairs as well. We didn’t use any language specific resource in the approaches which we proposed here. We have chosen two of the most