## **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, food item names, menu details, food manufacturing companies name, hotel names, restaurant names & addresses and more into Indian languages as localization is important without changing meaning. For better understanding, refer to the below examples: Example: | Type | English | Hindi | | --------- | --------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- | | Online Food App name | Zomato | जोमाटो | | Food Item name | Mushroom pepper masala | मशरूम पीपर मसाला | | Restaurant name | The Krishna Sagar | द कृष्णा सागर | | Hotel name | The Ritz-Carlton | द रिट्ज़-कार्लटन | ## **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 Food domain has domain specific abbreviations in-built. Abbreviation|Source |Transliterated ------------|-----------------|----------------- st |bakers st |बेकर्स स्ट्रीट bbq |bbq nation |बार्बेक्यू नेशन 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 ## 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 ## **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
Food	22
Names	2
Addresses	9

### 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": [ "Nestle" ] } ``` ## Response ``` { "responseList": [ { "apiStatus": 2, "inString": "Nestle", "outString": [ "नेस्ले" ] } ] } ```