My guest this month is Amba Kulkarni from the Department of Sanskrit at the University of Hyderabad, who has also been associated with IIT Kanpur and the National Sanskrit University. Professor Kulkarni is best known for her work linking traditional Indian linguistic theory (starting with Pāṇini and focussing on aspects such as Śabdabodha and Kāraka theory as studied especially within the Navya-Nyāya/'Neo-Logical' school of philosophy) and AI theories of Knowledge Representation to effect computer-based cognition of Sanskrit texts. Find out more about her recent book 'Sanskrit Parsing based on the theories of Śabdabodha' here.
The article by Rick Briggs that she mentions as her inspiration to apply her Computer Science background to Sanskrit is reprinted here, that by Rajeev Sangal and Vineet Chaitanya can be accessed here, and there is discussion of Bhāratīkṛṣṇa Tīrtha's book on Vedic Mathematics here.
She has collaborated extensively with Gérard Huet, best known in Sanskritist circles for his Sanskrit Heritage Site (part of which is the Segmenter). Relating to the parsing of the sentence yānaṃ vanaṃ gacchati 'the vehicle goes to the forest', she mentions the factors śabdabodha considers essential for verbal cognition: yogyatā or mutual compatibility, ākaṅksā or expectancy and saṃniddhi or proximity (read some discussion of these here). More on the three types of meaning of a word (abhidhā or literal, lakṣaṇā or metaphoric/extended and vyañjanā or suggested meaning) e.g. here.
If you are a Sanskritist interested in working in computational linguistics, Professor Kulkarni suggests a thorough focus in Kāvya/Kāvyaśāstra, Mīmāṃsā, Nyāya or