About

Transliteration is the process of converting texts from one script to another based on phonetic similarity. Here, the text is displayed in alphabets of different languages, but the pronunciation, grammar, and sense of the original version remain intact in these new characters. Transliteration is involved while converting the names, addresses, song titles, movie names, and more into Indian languages as localization is important without changing meaning.

For better understanding, refer to the below examples:
Example:

Type	English	Hindi
Movie Name	Mission Mangal	मिशन मंगल
Song Title	Dil mein mars hai	दिल में मार्स है
Artist Name	A R Rahman	ए आर रहमान

Features

Reverie’s Transliteration comes with unique features that have been tuned over years of working with Industry and Academia.

Abbreviations

Reverie’s Transliteration for Media has domain specific abbreviations in-built.

Abbreviation	Source	Transliterated
mr	mr India	मिस्टर इण्डिया
st	bakers st	बेकर्स स्ट्रीट
dr	dr kotnis ki amar kahani	डॉ. कोटनिस की अमर कहानी

It also intelligently understands whether the input word is an abbreviation or not. It tries to predict if the input word passed in CAPITAL letters needs to be converted into an abbreviation or should be treated as a normal word, also does the same for input words typed in lower case.

Source	Transliterated
YEQ Infra Mumbai	वाई.ई.क्यू. इन्फ्रा मुंबई
PEEL orange	पील ऑरेंज
asset twq kalyan nagar	ऐसेट टी.डब्ल्यू.क्यू. कल्याण नगर
URI: The Surgical Strike	उरी: द सर्जिकल स्ट्राइक

Disambiguation

Reverie’s Transliteration successfully identifies the context of a word used in the source content and then transliterates accordingly. This feature will decrease the editorial work as it can recognize the meaning of the word and help the native language users consume the content in the right order.

Example 1

Source Content	Transliterated Content
1st main, 3rd st, st. johns road	फर्स्ट मेन, थर्ड स्ट्रीट, सेंट. जॉन्स रोड

In the above example, the word st appears thrice:

Suffix for 1 (1st)
Acronym for Street
Acronym for Saint

The intelligent solution will automatically analyze the statement’s context and transliterate it as First, 3rd street, and Saint appropriately.

Example 2

Source Content	Transliterated Content
Singh Sahab the great, aap kahan the	सिंह साहब द ग्रेट, आप कहां थे

In the above example, the source content is written in English script (Latin Script), it consists of words of both English and Hindi languages. However, the word “THE” is used twice in the sentence:
as an adjective and once in the Hindi meaning “where were you?”.

Our API has successfully recognized the context and transliterated it accordingly.

Example 3

Source Content	Transliterated Content
dil me ho tum	दिल मे हो तुम
love me like you do	लव मि लाइक यू डू

Here the word ‘me’ is an ambiguous word. For the first sentence, it’s giving as मे and for the second sentence, it’s मि.
This is the unique feature of our API, where it can analyse the sentence of different languages and gives result accordingly.

Languages

Language	Language ISO Code
hindi	hi
marathi	mr
punjabi	pa
gujarati	gu
tamil	ta
telugu	te
malayalam	ml
kannada	kn
odia	or
assamese	as
bengali	bn

API Details

Header Details

Element	Type	Is Mandatory?	Description
src_lang	string	Yes	Source script to convert from.
tgt_lang	string	Yes	Target script to convert to.
domain	number	No	While domain parameter is optional, it gives better accuracy of conversion when you know what is the content that you are willing to convert. This is important as different proper nouns have their own nuances. This is an optional parameter Content Type Domain Music 25 Names 2

Body Details

Element	Type	Is Mandatory?	Description
data	array of content	Yes	List of input text for transliteration.

Sample Request & Response

Sample 1

Request

{
    "data": [
        "Mera Dil Bhi Kitna Pagal Hai"
    ]
}

Response

{
    "responseList": [
        {
            "apiStatus": 2,
            "inString": "Mera Dil Bhi Kitna Pagal Hai",
            "outString": [
                "मेरा दिल भी कितना पागल है "
            ]
        }
    ]
}

Sample 2

Request

{
    "data": [
        "Let me love you"
    ]
}

Response

{
    "responseList": [
        {
            "apiStatus": 2,
            "inString": "Let me love you",
            "outString": [
                "लेट मि लव यू "
            ]
        }
    ]
}