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Tamil NLP Technologies: Challenges, State of the Art, Trends and Future Scope

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Speech and Language Technologies for Low-Resource Languages (SPELLL 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1802))

Abstract

This paper aims to summarize the NLP-based technological development of the Tamil language. Tamil is one of the Dravidian languages that are serious about technological development. This phenomenon is reflected in its activities in developing language technology tools and the resources made for technological development. Tamil has successfully developed tools or systems for speech synthesis and recognition, grammatical analysis of grammar, semantics and social media text, along with machine translation. There are many types of research undertaken to orient towards this achievement. Similarly, many activities are developing resources to facilitate technological development. The activities include preparing text corpora for text including monolingual, parallel and lexical along with speech with lexical resources and grammar. What is needed now is to stock-take the achievement made so far and found out where Tamil is in the arena of technological development and looks forward further to its fast technological development. Computational linguistics in Tamil NLP is gaining more attraction, and various data sets available for research is highlighted in this work for further exploration.

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Notes

  1. 1.

    http://www.tamilvu.org/en/research-development.

  2. 2.

    https://tdil.meity.gov.in/Research_Effort.aspx.

  3. 3.

    https://github.com/nlpc-uom.

  4. 4.

    http://corpora.ciil.org/wordcorpora.htm.

  5. 5.

    http://www.emille.lancs.ac.uk/home.htm.

  6. 6.

    POS tagged corpus is available on request http://www.nlp.amrita.edu/nlpcorpus.html.

  7. 7.

    http://www.au-kbc.org/nlp/corpusrelease.html.

  8. 8.

    http://tdil-dc.in.

  9. 9.

    Parallel Corpus is available on request http://www.nlp.amrita.edu/nlpcorpus.html.

  10. 10.

    DPIL corpus is available on request http://www.nlp.amrita.edu/nlpcorpus.html.

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Acknowledgments

This paper is based on the White paper designed on the META-NET. We express our gratitude to Dr. George Rehm (Head of the META-NET), Prof. Joseph Mariani and Prof.Girish Nath Jha from School of Sanskrit and Indic Studies for the white paper development through close interactions. The complete resource links are available in the Tamil data portal, https://sites.google.com/view/tamilnlp.

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Authors and Affiliations

  1. CEN, Amrita Vishwa Vidyapeetham, Coimbatore, India

    S. Rajendran & K P Soman

  2. National Institute of Technology Karnataka, Surathkal, India

    M. Anand Kumar

  3. Vellore Institute of Technology, Chennai, India

    Ratnavel Rajalakshmi

  4. Pondicherry University, Pondicherry, India

    V. Dhanalakshmi

  5. National Institute of Technology, Tiruchirappalli, India

    P. Balasubramanian

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  1. S. Rajendran
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  3. Ratnavel Rajalakshmi
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  4. V. Dhanalakshmi
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  5. P. Balasubramanian
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  6. K P Soman
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Correspondence to M. Anand Kumar .

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Editors and Affiliations

  1. National Institute of Technology Karnataka, Mangalore, India

    Anand Kumar M

  2. National University of Ireland, Galway, Ireland

    Bharathi Raja Chakravarthi

  3. Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, India

    Bharathi B

  4. National University of Ireland, Galway, Ireland

    Colm O’Riordan

  5. Indian Institute of Technology Madras, Chennai, India

    Hema Murthy

  6. Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, India

    Thenmozhi Durairaj

  7. University of Hildesheim, Hildesheim, Germany

    Thomas Mandl

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Rajendran, S., Anand Kumar, M., Rajalakshmi, R., Dhanalakshmi, V., Balasubramanian, P., Soman, K.P. (2023). Tamil NLP Technologies: Challenges, State of the Art, Trends and Future Scope. In: M, A.K., et al. Speech and Language Technologies for Low-Resource Languages . SPELLL 2022. Communications in Computer and Information Science, vol 1802. Springer, Cham. https://doi.org/10.1007/978-3-031-33231-9_6

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