About the topic
Sanskrit as a candidate for Computer Language
About the topic
Receipt, Storage, Manipulation/Processing, Transfer and Retrieval of
The idea of using a natural language for computer programming is to
make it easier for people to talk to computers in their native tongue and
spare them the pain of learning a computer friendly language like
In natural language processing and related fields, study of complex
problems is required.
Sanskrit is considered to be one of the best structured language.
Richness, strength, accuracy, structure, flexibility and the extant work
available in Sanskrit.
So Sanskrit is a candidate for computer programming, in the fields of
natural language processing and Artificial Intelligence.
A historical Indo-Aryan language, the primary liturgical language of
Hinduism and a literary and scholarly language in Buddhism and Jainism.
Today, it is listed as one of the 22 scheduled languages of India and is an
official language of the state of Uttarakhand.
Member of the Indo-Iranian sub-family of the Indo-European family of
Closest ancient relatives are the Iranian languages Old Persian and
The earliest known linguistic activities date to Iron Age India(~8th century
BC)with the analysis of Sanskrit.
Computational linguistics is an interdisciplinary field dealing with the
statistical or rule-based modeling of natural language from a
When machine translation failed to yield accurate translations right
away, automated processing of human languages was recognized as far
more complex than had originally been assumed.
It was born as a new field of study devoted to algorithms for intelligently
processing language data.
In order to translate one language into another:
one had to understand the grammar of both languages, including both
morphology and syntax.
In order to understand syntax, one had to also understand the semantics and
the vocabulary, and even to understand something of the pragmatics of
Thus, what started as an effort to translate between languages evolved into an
entire discipline devoted to understanding how to represent and process
natural languages using computers.
Steps followed are:
Morphological and Lexical Analysis
Sanskrit as a candidate for Computer
Sanskrit is a strong candidate for Computer Language, in the fields of
Natural Language Processing and Artificial Intelligence. Because:
Analysis of Parts and forms of speech
Flexibility of Word-Formation
Structure of Grammar
Variety and richness of technical literature
One of the significant advantages of Sanskrit is that the grammar ensures
total precision and guards against ambiguity, miss-spelling and misspronunciation as the meanings are bound to get altered otherwise.
The real advantage is that the correlation between and spoken forms is
one, the two forms of input can be exchange ably used.
The analysis of alphabets (characters) is based on sound production from
well-defined places of utterances.
All valid words have proper derivation/deduction from finite set of well
grouped verb roots and noun bases so that what is meant is uniquely
determined and accuracy ensured.
Speech synthesis can possibly benefit by this feature immensely since
accent, frequency, emphasis and timing oriented discrepancies
associated with other natural language speech inputs are absent here.
Analysis of parts & forms of speech
From various categories of words in Sanskrit, a matrix of all possible valid
word forms can be generated by formalization of the grammar rules.
The grammar has simple effective rules for conversion between various
forms and sentences.
Flexibility in word-formation
All valid word-forms have 2 significant parts: the stem or substrate and the
With respect to the admissible combinations of substrates and
affixes, there are elaborate but clear rule specifying these with the
attendant changes in the meanings denoted, the latter being derivable
There cannot be distortions in Sanskrit either written or spoken and
violations of it will be transparent to the linguists.
Structure of grammar
All technical literature in Sanskrit have a fundamental set of „Aphorisms‟. These
are termed as “Sutras”
Grammar rule are in this „sutra‟ style which greatly condenses the amount of
instructions or information to be given to precisely convey a particular aspect.
They are contained in eight chapters with four quarters per chapter.
Verb-roots are grouped into 10 categories each having a given group
suffix, besides verb forming suffix added to the roots to form verbs.
Classification of verbs consists of six tenses and four moods in which verb can
There are 3 numbers as in the case of nouns and verb-roots can take one of 3
persons, ie first, second and third (I, you and It).
The absence of syntax in Sanskrit is a definite plus point in its favor. The
semantics also can be extracted by well laid out procedures.
Here the rule of syllogism and mimamsa are utilized. Mechanism of
associating meanings with words is dealt with in detail and guidelines for
establishing meanings at word, sentence and discourse level are given.
Rules to guide priority, conflicting handling, exception special cases are
well defined to ensure precision and accuracy.
There are numerous illustrations provided in works which includes
commentaries, treaties, notes and expositions, to explain the fundamentals
contained in sutras.
Variety and Richness of Technical
Technical literature comprises of 14 branches of learning.
4 vedas: rig veda, yajur veda, sama veda and atharveda veda
6 vedic auxiliaries: Phonology grammar, prosody, etymology, astronomy and
ritualry, study of vedic texts, syllogism, epics and codes of moral rectitude.
There is a great treasure of knowledge contained in these in an efficient
and streamlined manner.
Difference in approach to Language
The analysis of sentence was not based on Noun-Phrase model.
Sentence description was phrased in terms of a generative model: From a
action, agents, object, etc.) the structure of the sentence was derived so
that every word of a sentence could be referred back to the syntactic
Be it knowledge representation or speech synthesis, natural language
processing or machine translation, intelligent tutoring systems or
unambiguous semantic extraction, study of complex mathematical
problems or linguistics, in virtually any field, one can think of utilizing the
richness, strength, accuracy, efficiency, structure, flexibility and the extant
works available in the Sanskrit language.
Though variety of literature is available, we need to dispassionately study
these and take what is worth.