
This might make sense to those who are in the tech domain: AI translation for Konkani—especially across multiple scripts (Devanagari, Roman/Romi, Kannada)—is not a single “one-click” system working perfectly end-to-end. Instead, most systems combine three components: (1) neural machine translation (NMT) to convert meaning from source to target language, (2) script normalization, and (3) transliteration layers that map sounds into different writing systems.
Techies keep calling Konkani a "low-resource (limited training data)" data. I suspect much of the text produced over decades and even centuries have not been scanned; and if they have been scanned in government/taxpayer-funded projects, these have not been adequately shared or utilised. Many digitisation projects have been announced in Goa since even the 1980s and 1990s, but what's the outcome of this is not exactly clear. Systems like Google Translate often rely on broader Indian-language models and then approximate output, especially for Roman script, which is usually generated via phonetic transliteration rather than a native Konkani orthographic model.
Current research-grade systems like AI4Bharat’s IndicTrans2 (used in academic and open-source Indic NLP work) are believed to outperform commercial tools for many Indian languages, including Konkani. These have trained specifically on multilingual Indic corpora and supposedly handle script mapping more consistently. They might lack user interfaces that the commercial tools have. Microsoft Translator and Google’s system are blaming the limited training data and uneven coverage across scripts for their lack of accuracy.
Another interesting tool is Konkanverter.com. It works quite well for basic Romi transliteration, especially when converting from Devanagari or Kannada into Roman script in a consistent, rule-based way. Its strength is that it follows a standardised orthography model, so outputs are fairly predictable and useful for learners or documentation. It is however still a rule-based transliteration engine, not a dialect-aware AI system. So it does not truly “understand” spoken variation or regional pronunciation differences.
Konkanverter.com sometimes struggles with dialectal variation and ambiguity in Goan sub-dialects (Bardez, Saxtti, Antruz) and Catholic vs Hindu usage differences. Many Konkani words change pronunciation and vowel quality across regions, but Konkanverter generally maps one standard form rather than adapting to those shifts. It has been called a clean script converter, not a dialect-sensitive transliteration AI. It performs well for formal text but only moderately for capturing real-world spoken variation. I find it rendering Romi script better than others.
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On Apr 14, 2026, at 12:43 PM, Frederick Noronha <frederic...@gmail.com> wrote:
Prof John and all,
Google Translate handles Konkani only moderately well. Its performance varies widely depending on the dialect, script (Devanagari, Roman, Kannada, Malayalam, Perso-Arabic), and sentence complexity. It manages simple phrases and everyday communication. But it struggles with literary or technical texts. Especially those involving regional idioms or culturally specific expressions. It often produces awkward or inaccurate results. This could be because of its relatively limited digital corpus for Konkani compared to major languages. It’s a helpful starting tool, but not fully reliable for precise or complex translation. At the moment, it is focussed on Nagari (Devanagari) Konkani, though Romi abilities were also promised in the past. See Meet the Goan American who Mangified Google Translate in Konkani | Prudent Media Goa https://www.youtube.com/watch?v=J9Mh0VcPD20
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On Apr 14, 2026, at 9:25 PM, William Robert Da Silva <wrds...@gmail.com> wrote:
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Sandra Ataíde Lobo
On Apr 15, 2026, at 6:15 AM, Sandra Ataíde Lobo <sandr...@netcabo.pt> wrote: