Toward a deep dialectological representation of

Cathcart, Chundra

doi:10.18653/v1/w19-1411

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…Some of these sources have been used in previous work on South Asian historical linguistics, e.g. Cathcart and Rama (2020); Cathcart (2019bCathcart ( ,a, 2020-this is the first attempt to consolidate them. Note some previous work in this direction: while the SARVA project (Southworth, 2005) did not reach fruition, a searchable database of Dravidian cognates was developed by Suresh Kolichala under its auspices.…”

Section: Jambu Etymological Databasementioning

confidence: 99%

Computational historical linguistics and language diversity in South Asia

Arora¹,

Farris²,

Basu³

et al. 2022

Preprint

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South Asia is home to a plethora of languages, many of which severely lack access to new language technologies. This linguistic diversity also results in a research environment conducive to the study of comparative, contact, and historical linguistics-fields which necessitate the gathering of extensive data from many languages. We claim that data scatteredness (rather than scarcity) is the primary obstacle in the development of South Asian language technology, and suggest that the study of language history is uniquely aligned with surmounting this obstacle. We review recent developments in and at the intersection of South Asian NLP and historical-comparative linguistics, describing our and others' current efforts in this area. We also offer new strategies towards breaking the data barrier.

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Section: Jambu Etymological Databasementioning

confidence: 99%

Computational historical linguistics and language diversity in South Asia

Arora¹,

Farris²,

Basu³

et al. 2022

Preprint

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In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonology

Cathcart¹,

Wandl²

2020

Proceedings of the 17th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology

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This paper investigates the ability of neural network architectures to effectively learn diachronic phonological generalizations in a multilingual setting. We employ models using three different types of language embedding (dense, sigmoid, and straight-through). We find that the Straight-Through model outperforms the other two in terms of accuracy, but the Sigmoid model's language embeddings show the strongest agreement with the traditional subgrouping of the Slavic languages. We find that the Straight-Through model has learned coherent, semi-interpretable information about sound change, and outline directions for future research.

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Bhāṣācitra: Visualising the dialect geography of South Asia

Arora¹,

Farris²,

Gopalakrishnan³

et al. 2021

Proceedings of the 2nd International Workshop on Computational Approaches to Historical Language Change 2021

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We present Bhās .ā citra, 1 a dialect mapping system for South Asia built on a database of linguistic studies of languages of the region annotated for topic and location data. We analyse language coverage and look towards applications to typology by visualising example datasets. The application is not only meant to be useful for feature mapping, but also serves as a new kind of interactive bibliography for linguists of South Asian languages.

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Toward a deep dialectological representation of

Cited by 3 publications

References 24 publications

Computational historical linguistics and language diversity in South Asia

Computational historical linguistics and language diversity in South Asia

In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonology

Bhāṣācitra: Visualising the dialect geography of South Asia

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