T. V. Geetha

Also published as: Geetha T V, T V Geetha


2022

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Building and Analysis of Tamil Lyric Corpus with Semantic Representation
Karthika Ranganathan | Geetha T V
Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Workshop 2: Corpus Generation and Corpus Augmentation for Machine Translation)

In the new era of modern technology, the cloud has become the library for many things including entertainment, i.e, the availability of lyrics. In order to create awareness about the language and to increase the interest in Tamil film lyrics, a computerized electronic format of Tamil lyrics corpus is necessary for mining the lyric documents. In this paper, the Tamil lyric corpus was collected from various books and lyric websites. Here, we also address the challenges faced while building this corpus. A corpus was created with 15286 documents and stored all the lyric information obtained in the XML format. In this paper, we also explained the Universal Networking Language (UNL) semantic representation that helps to represent the document in a language and domain independent ways. We evaluated this corpus by performing simple statistical analysis for characters, words and a few rhetorical effect analysis. We also evaluated our semantic representation with the existing work and the results are very encouraging.

2012

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Semantic Parsing of Tamil Sentences
Balaji Jagan | Geetha T V | Ranjani Parthasarathi
Proceedings of the Workshop on Machine Translation and Parsing in Indian Languages

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Two-Stage Bootstrapping for Anaphora Resolution
Balaji Jagan | T V Geetha | Ranjani Parthasarathi
Proceedings of COLING 2012: Posters