Integral Part Of Natural Language Processing English Language Essay

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Abstract:-Machine Translation is one of the central areas of focus of Natural Language Processing where translation is done from Source Language to Target Language preserving the meaning of the sentence. Large amount of research is being done in this field. However, research in Machine Translation remains highly localized to the particular source and target languages due to the large variations in the syntactical construction of languages. Inflection is an important part to get the correct translation. Inflection is basically the adding of appropriate suffix to the word according to the sentence structure to obtain the meaningful form of the word. This paper presents the implementation of the Inflection for English to Marathi Translation. The inflection of Nouns, Pronouns, Verbs, Adjectives are done on the basis of the other words and their attributes in the sentence. This paper gives the rules for inflecting the above Parts-of-Speech.

Keywords: Natural Language Processing, Machine Translation, Parsing, Marathi, Parts-Of-Speech, Inflection, Vibhakti, Prataya, Adpositions, Preposition, Postposition, Penn Tags.

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INTRODUCTION

Machine translation, an integral part of Natural Language Processing, is important for breaking the language barrier and facilitating the inter-lingual communication. Marathi, an Indo-Aryan language derived from Sanskrit, is spoken by 70 million people in India. The script currently used in Marathi is called "baalbodha" which is a modified version of Devnagri Script [1]. While translating one language to another changing of the word order and its form according to the grammar of the target language is very important. For the scope of this paper the Source Language is English and Target Language is Marathi.

WORD ORDERING IN LINGUISTICS

The syntactic structure of a language is determined by the word order. Words are classified into 8 parts-of-speech (POS) [noun, pronoun, adjective, verb, conjunction, preposition, interjection]. The arrangement of these POS in sentences is determined according to the structure the language follows. English follows Subject-Verb-Object (SVO) structure while Marathi follows Subject-Object-Verb (SOV) structure [2].Along with Marathi other Indo-Aryan language like Hindi, also follow the SOV structure.

IMPORTANCE OF ADPOSITIONS IN LINGUISTICS

Adpositions are words which can occur before or after a phrase, word, or a clause that is necessary to complete the meaning of a given sentence. Adpositions are mainly categorized as:

Prepositions

Postpositions

Circumpositions

Prepositions

Prepositions are defined as the words placed before the complement [3]. Prepositions are used in English.

Example:

I value my family above everything else.

Postpositions

Postpositions are words which come after the complement.[2] Postpositions are used in Marathi, Hindi, Urdu, Korean, Turkish, and Japanese.

Example:

Ekh ckdh izR;sd xks'Vh is{kk ekb&;k dqVqackyk tkLr egRo nsrks .

Circumpositions

Circumpositions are words that appear on both sides of the complement. They are used in English, Dutch, Swedish, and French.

Example:

I will exercise regularly from now on.

The languages which follow SOV Structure use postpositions. Hence, while translating an English sentence.

(SVO structure) to a Marathi sentence (SOV structure), we need to change the prepositions (of English) to postpositions (of Marathi). This is a major issue which needs to be resolved for inflecting the nouns, verbs and cases (Vibhakti).

INFLECTION

Generating inflection of a word is important to retain the correct form of the word in Marathi. Words can be classified in two types depending on the Inflection as [1]:

Inflectional Words:

Noun

Pronoun

Adjective

Verb

Non-Inflectional Words:

Adverb

Preposition

Interjection

Conjunction

The words are inflected on the basis of changing Gender (Masculine, Feminine, Neuter), Multiplicity (Singular, Plural), Tense (Present, Past, Future), and Case (Nominative, Accusative, Instrumental, Dative, Ablative, Genitive, Locative, Vocative).

Noun Inflection

Noun inflection is performed on the basis of change in Gender, Multiplicity or Case (Vibhakti). The inflection of a word can be determined from the word endings. Following table describes the word endings and its inflections.

TABLE I

TERMINATING VOWEL OF ITS ROOT [2].

Terminating Vowel of the Root

Plural Inflection

Masculine

Feminine

Neuter

v

No change

vk bZ

,

vk

,

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vk

…

b

No change

No change

No change

bZ

No change

vk ;k

,

m

No change

No change

No change

mw

No change

v

,

,

…

vk

bZ

Z,s

…

vk

…

vks

No change

vk

…

vkS

No change

…

…

The above table will be found helpful in determining the plural form of a noun by terminating vowel of its root. For instance, the plural form of "ck;dks" must be "vk" making up "ck;dk" as "vk" stands opposite to the vowel "vks" in the column super scribed Feminine[2].

The word "xk;" must be inflected to "xk;h" as "v" would be replaced by "bZ". Another example of a word-ending in "bZ", "ik;jh" would get inflected as "ik;j~;k" wherein ";k" is the word ending.

Case is an inflected form of Noun by which its relation to other words in the sentence is indicated.

For example:

He drove the car.

"R;kus xkMh pkyoyh"

TABLE II

CASE TERMINATIONS [2].

Case (Vibhakti)

Singular

Plural

Nominative

---

---

Accusative

l ] yk

l ] uk

Instrumental

us] f"k

uh f"k

Dative

l ] yk

l ] uk

Ablative

gwu mwu

gwu mwu

Genitive

pk]ph]ps

pk]ph]ps

Locative

r

r

Vocative

---

uks

Verb Inflection

When we translate the verb using Marathi Dictionary we get the gerundial form i.e it is given with the particle ".ks".

Example:

"[ksG.ks" - to play

For inflecting the verb, first we need to derive the verbal root (/kkrq) and then add personal endings to it, to indicate its relation to the noun. We can get verbal roots by dropping the particle ".ks" from the gerundial form Inflection of the verb depends upon the following particulars:

The Gender (fyax): Masculine, Feminine and Neuter.

The Number (opu): Singular, Plural.

Person (iq#'k): First, Second and Third.

Tenses (dkG): Present, Past and Future.

Sometimes personal endings may also depend on moods (vFkZ), the constructions (iz;ksx), the participle and the verbal nouns (/kkrqlk/khrs) [2].

The table for verb inflection is given below (Table no. III).

TABLE III

RULES FOR DHAATU TO VERB [1].

Adjective inflection

Adjective is a verb which is joined to a noun to qualify it. Inflection of adjective depends upon gender, multiplicity, attachment of postpositions to the noun modified by such objective. When genitive case makers or some prepositions are attached to nouns, it produces adjective [4].

TABLE IV

ADJECTIVE TERMINATION FOR "vk" [4]

Changing part in masculine form

Feminine

Neuter

Oblique form

vk

bzzZ

,

;k

Pronoun inflection

A pronoun is a word that can be substituted for a noun or a noun phrase.Pronoun inflection is similar to noun inflection but there are some special cases which need to handle seperately. For the verbs such as "like", "want", "will", "need" and "would", the pronoun inflection are different than general cases. Some sentences have the same structure alongwith the parse tree, gender, multiplicity, cases but have different translation of pronoun. These sentences will typically include the above mentioned verbs.

Following table determines the translation of pronouns if the sentence has any of the verbs "like", "want", "will", "need" or "would".

TABLE V

EXCEPTIONAL PRONOUN INFLECTION.

English word

Multiplicity

Marathi

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I

S

eyk

We

P

vkEgkyk

You

S

rqyk

You

P

rqEgkyk

He

S

R;kyk

She

S

fryk

They

P

R;kauk

Following cases gives a comparison of different cases where the same pronoun is used but has different inflections depending upon the verbs used in the sentence.

Case 1 :( First person singular)

Example 1:

English sentence: I play football.

Parse Tree:

Marathi translation(After inflection):

eh [ksGrks QqVckWy++-

Example 2:

English sentence: I like mango.

Parse Tree:

Marathi translation(After Inflection):

eyk vkoMrks vkack-

Case 2:(first person plural)

Example 1:

English sentence: We are friends.

Parse Tree:

Marathi translation(After inflection):

vkEgh vkgksr fe=-

Example 2:

English sentence: We need books.

Parse Tree:

Marathi translation(After inflection):

vkEgkyk ikfgts iqLrd-

Case 3: (Second Person Singular)

Example 1:

English sentence: What do you do?

Parse Tree:

Marathi translation(After inflection):

dk; rq djr vkgs\

Example 2:

English sentence: What do you like?

Parse Tree:

Marathi translation(After inflection):

dk; rqyk vkoMra\

Case 4: (Second person plural)

Example 1:

English sentence: You should do this.

Parse Tree:

Marathi translation(After inflection):

rqEgh ikghts djk;yk gs-

Example 2:

English sentence: You will get this.

Parse Tree:

Marathi translation(After Inflection):

rqEgkyk feGsy gs-

Case 5: (Third person singular)

Example 1:

English sentence: He lies.

Parse Tree:

Marathi translation(After inflection):

rks [kksVa cksyrks-

Example 2:

English sentence: He wants.

Parse Tree:

Marathi translation(After inflection):

R;kyk ikghts-

Case 6:- (Third person plural)

Example 1:

English sentence: They play cricket.

Parse Tree:

Marathi translation(After Inflection):

rs [ksGrkr fddsV-

Example 2:

English sentence: They need money.

Parse Tree:

Marathi translation(After Inflection):

R;kauk ikfgts iSls-

In all the above cases, the first example gives the inflection of pronouns according to the general inflection rules and the second examples give the inflection of pronoun according to the rules defined in Table 5.

IMPLEMENTATION OF INFLECTION

For implementation of the inflection we need to store following information to the database.

TABLE VI

DICTIONARY FORMAT

English

word

POS

Tag

Gender

Tense

Multiplicity

Degree

Case

POS tags are identified from parser.

Gender tags are identified from word endings or the gender of the word stored in a dictionary.

Tense of the sentence can determined from Penn tags that we get from the parser. Following table gives PENN tags and it's tense:

TABLE VII

GETTING THE TENSE FROM THE PENN TAGS

Penn_Tag

Tense

VB,VBG,VBP,VBZ

Present

VBD,VBN

Past

MD

Future

Multiplicity can also be determined from Penn tags. Following table gives PENN Tags and its multiplicity:

TABLE VIII

GETTING THE MULTIPLICITY FROM THE PENN TAGS

Penn_Tag

Multiplicity

NN,NNP,VBD,VB,VBZ

S

NNS,NNP

P

The case of the noun is determined on the basis of subject, object or prepositions.

The degree of the person can be determined from the following table:

TABLE IX

GETTING THE DEGREE DEPENDING UPON THE PERSON

Person

Degree

I, Me, My, Mine, We, Our, Us.

1

You, Your, Yours

2

He, She, It, They, His, Him, Her, Them, Their.

3

Using the above retrieved information, we can apply various Inflection rules given in the above sections to get the correct inflection. The inflected words can then be mapped to the SVO structure of Marathi to get the correct translation.

Example:

English Sentence:

He came to my house to meet Maya but she was not there.

Parse Tree:

TABLE X

RULES FOR INFLECTION

Eng_Word

Marathi_Lemma

Inflected_Word

Rules to get Inflected

He

rks

rks

_____

came

;s.ks

vkyk

Verb table, 3rd person, Masculine, Singular, Past Tense.

to

yk

my

ek>a

ekÃ-;k

Nominative Singular. Hence no change.

house

?kj

?kjh

Case table, Locative Singular.

to

yk

_____

_____

meet

HksV.ks

HksVk;yk

Case table, Dative Singular.

Maya

ek;k

ek;kyk

Case table, Accusative Singular.

but

i.k

i.k

_____

she

rh

rh

_____

was

gksrh

uOgrh

_____

not

ukgh

_____

there

frFks

frFks

_____

CONCLUSION

In the field of Machine Translation for Indian Languages a great amount of work has been done bur for Marathi the research is limited. This paper focuses on the issue of English to Marathi Translation with proper Inflection. The main objective of this paper is to give the detailed description of the rules required for inflecting the words.

ACKNOWLEDGEMENT

The authors would like to thank MIT College of Engineering, Pune and Board of College and University Development (BCUD), University of Pune for the grant for conducting the research work for Multi-Lingual Machine Translation System under which the paper has been written.