Sanskrit software language

Designed for professional use. License Lipikaar comes with a per PC license. Once purchased, it can be used on a single PC without any additional charges. To continue using the software after 3 days, purchase and activation is required.

Click here to know details. Help Click here to view detailed help for Sanskrit Typing. You can also see the FAQ page. If you have any questions, write to. What is Lipikaar? This means, you will be able to do simple tasks such as writing email text in Sanskrit, create short stories, write articles, prepare a report, create a office notice, etc in Sanskrit language.

This is a set of fonts which can be used while creating the contents in Sanskrit language. These fonts are Unicode compliant and hence adheres to storage standard. These are aesthetically good looking fonts in Normal weight. This setup will install all three softwares mentioned below on your computer.

This setup will install all three softwares mentioned below on your computer: 1. Make a note. The conclusion of the paper was that humans are capable of using an extremely precise unambiguous language. That should save you some back and forth when we debunk baseless claims. Sanskrit is a brilliant language. It really is the most precise language in existence, with Latin being a close second. Sanskrit makes use of declensions in nearly every part of speech.

The rules of inflections are precise. Just by knowing the ends of a word, one could know its role in a sentence. This makes word order a non issue.

A three word sentence could be written six different ways and a four word sentence in twenty four. None of the permutations would alter their meaning. Because of the use of declensions, a lot of information is packed in fewer words. This makes transmission of information extremely efficient in speech. Sanskrit is not the only language that can do this though. Latin, an equally dead language, also allowed word order independent sentences in a similar way.

Latin too had quite a complicated set of grammar rules. Despite the arguably best verbal efficiency, there are a few issues with the language in actual knowledge representation. Sanskrit has a glyph based script rather than the alphabet based script as with Latin and its derivatives.

Latin alphabets take one byte of space each. Sanskrit written in the current character set for the Devanagari script is however not an efficient way of storing information. Latin script, on the other hand, is consistent. You spend exactly the same number of bytes in conveying a message as the number of letters it contains.

If the character set were redone to start with Devanagari characters rather than the Latin ones, they could reduce space consumption to about a half.

It does not have a universal phonology. A native speaker of a Sanskrit derived language will find it hard to sound in other languages. Nearly everything about Sanskrit, as is known today, was codified sometime around the year BCE by one person, Panini , who was bent on making it as precise and concise as was humanly possible. It is indeed the work of a primitive computer scientist without the hardware.

This is not to say Panini intended for his language to be used with machines. At best, his work caught the eye of a pattern seeking human in need of an answer to a difficult, perhaps unsolvable problem — it was bound to happen sooner or later.

The Sanskrit of today, the one reportedly spoken by a few tens of thousands, is about the same as that codified two and a half millennia ago. Unlike natural languages, speakers of Sanskrit cannot be classified as proficient or eloquent as its precision does not allow gradations.

Even artificial languages do not suffer that restriction. Sanskrit was never widely spoken. During the past two and a half millennia, Sanskrit scholarship was an exclusive club. None other than the Brahmins were allowed to use it. That all literary works in Sanskrit was made accessible only to the Brahmins, spelt its doom. The thing about languages is that, like living organisms, languages too evolve by natural selection.

Natural languages thrive by fitting the need of the era. The flexible of the lot flourish organically forcing the less prominent ones to wither away.

This is essentially why every attempt to revive the language will fail, no exceptions. The paper does not at all contain any claim, mention or indication that Sanskrit can be used as a programming language. The subject was a programmer. The question Briggs tried to answer was whether it was possible for one to create a perfect language for knowledge representation. If a computer scientist were to codify a new language humans could use just as well as a machine, what would the end result look like?

He then shows how Sanskrit manages to fulfil all of those requirements. To him, it was astonishing to find that someone who lived a long while ago could accomplish such a feat of brilliance; the entire piece is a recurring acknowledgement of that fact.

Even after all of that, he never once suggested that Sanskrit should be used for knowledge representation. He insisted however that if anyone attempted to create such a language, they would do well to follow a similar pattern of processes as Panini did with Sanskrit.

Briggs did get a few things wrong in his piece. There are, however, a few fallacies he seemed to have overlooked. Sanskrit however is capable of all of those, its literature being a glaring proof of it. Without exactly those seven, the totality of Sanskrit works would see their volume reduced to about a quarter. The degree of precision that Sanskrit affords its speakers prevents verbosity i. Attempts at verbosity leads to a redundant prose.

Translating to Sanskrit from any other language would thus lead to loss of data. A language that attains precision does so at the expense of creativity. People who praise Sanskrit for its precision are the same people who suggest that works in the language need interpretation by scholars. Every single hoax about Sanskrit as programming language can be traced back to it.

It is possible that the paper just gets quoted a lot for having kickstarted all of that research into Sanskrit. The logical next question is, is there any research at all? So, I dedicated about two hours of my info-binging time to look up research related to Sanskrit. Every research that relates to both, the language and computation, are conducted under dedicated Sanskrit research academies based in India.

However, there is none to back the claims about Sanskrit gaining a foothold in modern computing. Well, good… pretty good actually. Shazam and SoundHound can tell you what song is playing around you. Oh Siri! How could I forget about that? Besides, give it some hard thought for a moment. It raises a few questions. Foremost, what exactly will that accomplish?

Sure, a native Sanskrit speaker will not be disappointed when a computer understands everything they say. Would anyone on this planet be willing to learn Sanskrit just to clearly communicate their ideas to a machine? Of course not. If a fifth of the world or even a fiftieth spoke the language, it would make some sense. A fiftieth is still ten thousand times larger than the self-reported Sanskrit speaking population. See, when nearly all programs are written in English, there is little incentive for programmers to pursue exotic languages.

Again, this does not mean a Sanskrit parser can never be created. It can, but the efforts will have to come from those who actually care about it. Sanskrit is the second official language in the Indian state of Uttarakhand. It had a population of a little over 10 million as in the census. The number of people who declared Sanskrit as their native language in the census was a bit over 14 thousand. Yes, that can be explained by misplaced pride, extreme nationalism and a hint of idiocy.

Another important question: Why not focus our efforts on writing AI that understands normal humans speech rather than structured speech? Teaching the world that language to simplify the work of developers of natural language parsers — that would be reinventing the wheel. How are AI researchers planning to solve that problem? Instead of dissecting every statement into its constituent words, natural language parsers use a statistics intensive approach to guess their actual meaning.

Inputs are compared with massive databases of previously parsed information. Based on the context, the interpretation engine would determine the one that was most probably meant. The system will also have a parallel rating component that would evaluate whether it output the right thing. Over a large enough duration, by collecting and consolidating the information gained from a lot of users, the system would get better at understanding natural languages.

It constantly borrows words from other languages for their own use. When new non-existent words become mainstream, they embrace rather than despise. It thrives by adaptation.