We discuss the development of kelvi.ca, an open source web-based dictionary and morphological parser designed to aid Tamil learners in developing their literacy skills. Tamil is an agglutinative language and heavily suffixal. Existing Tamil dictionaries only carry stems, not conjugated or inflected forms, and for a beginner learner of the language, isolating the stem in an unfamiliar word can be very challenging. Kelvi provides 1) the stem of any input word alongside its definition, and 2) non-technical descriptions of any suffixes that are part of this input, so that learners will gradually start to recognize these suffixes and be able to understand and produce new Tamil words themselves. In detailing our process of collaborative research, user interviews, suffix database creation, and error analysis, we also hope to show that Kelvi can be adapted for other languages and has the potential to be a useful pedagogical aid for learner literacy development, especially for agglutinative and/or polysynthetic languages which tend to be otherwise underserved in the mainstream.

This paper describes the motivation and implementation details for a rule-based, index-preserving grapheme-to-phoneme engine ‘G_i2P_i' implemented in pure Python and released under the open source MIT license. The engine and interface have been designed to prioritize the developer experience of potential contributors without requiring a high level of programming knowledge. ‘G_i2P_i' already provides mappings for 30 (mostly Indigenous) languages, and the package is accompanied by a web-based interactive development environment, a RESTful API, and extensive documentation to encourage the addition of more mappings in the future. We also present three downstream applications of ‘G_i2P_i' and show results of a preliminary evaluation.