The Multilingual Language Recognition API is engineered to automatically detect and determine the language used in any given text or character string. By employing advanced algorithms and linguistic analysis, this API seamlessly integrates into diverse applications and systems, delivering precise and dependable language detection capabilities.
Fundamentally, the Multilingual Language Recognition API functions by analyzing the inherent structural and grammatical patterns within the provided text. Through the application of statistical models and machine learning techniques, the API discerns the unique characteristics associated with different languages, enabling informed predictions about the language utilized in the text.
A significant advantage of the Multilingual Language Recognition API is its ability to accurately identify a broad array of languages from around the world. Whether the text is in widely spoken languages such as English or Spanish, or less common languages like Catalan or Bosnian, the API excels in recognizing and categorizing the language with high accuracy.
Moreover, the Multilingual Language Recognition API accommodates text inputs of varying lengths, from short sentences to lengthy paragraphs. This flexibility empowers users to seamlessly integrate language detection functionality into a wide range of applications, spanning from basic text analysis tools to sophisticated natural language processing systems.
Designed for scalability, the API efficiently manages substantial volumes of text input with minimal latency. This scalability makes it well-suited for deployment in environments requiring rapid language detection, such as real-time chat applications, social media monitoring platforms, or extensive content moderation systems.
In essence, the Multilingual Language Recognition API provides automated language identification with extensive language support and exceptional accuracy. It is suitable for diverse applications across various industries, enabling seamless integration of language detection functionality into applications and systems.
It will receive parameters and provide you with a JSON.
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To use this endpoint you just have to run it and you will get the languages available to detect.
[{"name":"Afrikaans","code":"af","accuracy":0.7879901960784313,"datapoints":1632},{"name":"Amharic","code":"am","accuracy":1,"datapoints":3},{"name":"Aragonese","code":"an","accuracy":0.5,"datapoints":4},{"name":"Arabic","code":"ar","accuracy":0.9978312977970552,"datapoints":8761},{"name":"Assamese","code":"as","accuracy":0.8635416666666667,"datapoints":960},{"name":"Bashkir","code":"ba","accuracy":0.95,"datapoints":120},{"name":"Belarusian","code":"be","accuracy":0.9625779625779626,"datapoints":6253},{"name":"Bulgarian","code":"bg","accuracy":0.9869885139985642,"datapoints":11144},{"name":"Bengali","code":"bn","accuracy":1,"datapoints":1164},{"name":"Tibetan Standard","code":"bo","accuracy":1,"datapoints":20},{"name":"Breton","code":"br","accuracy":0.9543043655650755,"datapoints":2451},{"name":"Bosnian","code":"bs","accuracy":0.03597122302158273,"datapoints":139},{"name":"Catalan","code":"ca","accuracy":0.8833862433862434,"datapoints":4725},{"name":"Chechen","code":"ce","accuracy":0.7142857142857143,"datapoints":7},{"name":"Corsican","code":"co","accuracy":0.2,"datapoints":5},{"name":"Czech","code":"cs","accuracy":0.9898738838258307,"datapoints":10863},{"name":"Chuvash","code":"cv","accuracy":0.9543478260869566,"datapoints":460},{"name":"Welsh","code":"cy","accuracy":0.8917609046849758,"datapoints":619},{"name":"Danish","code":"da","accuracy":0.948035819334597,"datapoints":15299},{"name":"German","code":"de","accuracy":0.9998637230853094,"datapoints":22014},{"name":"Divehi","code":"dv","accuracy":1,"datapoints":15},{"name":"Greek","code":"el","accuracy":1,"datapoints":12039},{"name":"English","code":"en","accuracy":1,"datapoints":22428},{"name":"Esperanto","code":"eo","accuracy":0.999551594641556,"datapoints":17841},{"name":"Spanish","code":"es","accuracy":0.998134635430954,"datapoints":18227},{"name":"Estonian","code":"et","accuracy":0.9356153219233904,"datapoints":1227},{"name":"Basque","code":"eu","accuracy":0.9676558852950984,"datapoints":2999},{"name":"Finnish","code":"fi","accuracy":0.9990807767436516,"datapoints":17406},{"name":"French","code":"fr","accuracy":0.999523314265904,"datapoints":23076},{"name":"Western Frisian","code":"fy","accuracy":0.6635514018691588,"datapoints":107},{"name":"Irish","code":"ga","accuracy":0.9065743944636678,"datapoints":867},{"name":"Gaelic","code":"gd","accuracy":0.8966789667896679,"datapoints":542},{"name":"Galician","code":"gl","accuracy":0.5790679908326967,"datapoints":2618},{"name":"Gujarati","code":"gu","accuracy":1,"datapoints":57},{"name":"Manx","code":"gv","accuracy":0,"datapoints":6},{"name":"Hebrew","code":"he","accuracy":1,"datapoints":8616},{"name":"Hindi","code":"hi","accuracy":0.999627004848937,"datapoints":5362},{"name":"Croatian","code":"hr","accuracy":0.5333033303330333,"datapoints":2222},{"name":"Haitian","code":"ht","accuracy":0.06666666666666667,"datapoints":15},{"name":"Hungarian","code":"hu","accuracy":0.9996655891204994,"datapoints":17942},{"name":"Armenian","code":"hy","accuracy":0.9980694980694981,"datapoints":518},{"name":"Interlingua","code":"ia","accuracy":0.7500798636992866,"datapoints":18782},{"name":"Indonesian","code":"id","accuracy":0.949637217242851,"datapoints":9372},{"name":"Interlingue","code":"ie","accuracy":0.4718485301444943,"datapoints":2007},{"name":"Ido","code":"io","accuracy":0.48055077452667816,"datapoints":2905},{"name":"Icelandic","code":"is","accuracy":0.9803582652419862,"datapoints":6364},{"name":"Italian","code":"it","accuracy":0.9989632216522972,"datapoints":18326},{"name":"Japanese","code":"ja","accuracy":1,"datapoints":2169},{"name":"Javanese","code":"jv","accuracy":0.6461538461538462,"datapoints":260},{"name":"Georgian","code":"ka","accuracy":1,"datapoints":1973},{"name":"Kazakh","code":"kk","accuracy":0.9802867383512545,"datapoints":2232},{"name":"Khmer","code":"km","accuracy":0.9920844327176781,"datapoints":379},{"name":"Kannada","code":"kn","accuracy":1,"datapoints":118},{"name":"Korean","code":"ko","accuracy":1,"datapoints":482},{"name":"Cornish","code":"kw","accuracy":0.8779342723004695,"datapoints":426},{"name":"Kyrgyz","code":"ky","accuracy":0.8787878787878788,"datapoints":66},{"name":"Latin","code":"la","accuracy":0.9206085511934948,"datapoints":11437},{"name":"Luxembourgish","code":"lb","accuracy":0.5944700460829493,"datapoints":217},{"name":"Limburgish","code":"li","accuracy":0.3333333333333333,"datapoints":3},{"name":"Lao","code":"lo","accuracy":1,"datapoints":70},{"name":"Lithuanian","code":"lt","accuracy":0.9933501987712324,"datapoints":13835},{"name":"Latvian","code":"lv","accuracy":0.9597747385358005,"datapoints":1243},{"name":"Macedonian","code":"mk","accuracy":0.9959903214656066,"datapoints":14465},{"name":"Malayalam","code":"ml","accuracy":1,"datapoints":517},{"name":"Marathi","code":"mr","accuracy":0.9995220342223496,"datapoints":10461},{"name":"Maltese","code":"mt","accuracy":0.8076923076923077,"datapoints":52},{"name":"Burmese","code":"my","accuracy":1,"datapoints":216},{"name":"Dutch","code":"nl","accuracy":0.9934780393355752,"datapoints":19626},{"name":"Norwegian Nynorsk","code":"nn","accuracy":0.7990867579908676,"datapoints":657},{"name":"Occitan","code":"oc","accuracy":0.7679133170220203,"datapoints":2861},{"name":"Ossetian","code":"os","accuracy":0.9830508474576272,"datapoints":59},{"name":"Panjabi","code":"pa","accuracy":1,"datapoints":88},{"name":"Polish","code":"pl","accuracy":0.999718595227375,"datapoints":17768},{"name":"Portuguese","code":"pt","accuracy":0.9933082184990581,"datapoints":20174},{"name":"Romansh","code":"rm","accuracy":0.0625,"datapoints":16},{"name":"Romanian","code":"ro","accuracy":0.9886430678466077,"datapoints":13560},{"name":"Russian","code":"ru","accuracy":0.9997114663281205,"datapoints":17329},{"name":"Sanskrit","code":"sa","accuracy":0.7272727272727273,"datapoints":11},{"name":"Sinhala","code":"si","accuracy":1,"datapoints":9},{"name":"Slovak","code":"sk","accuracy":0.8263157894736842,"datapoints":4370},{"name":"Slovene","code":"sl","accuracy":0.6774193548387096,"datapoints":372},{"name":"Somali","code":"so","accuracy":0.21875,"datapoints":32},{"name":"Serbian","code":"sr","accuracy":0.8489699125537276,"datapoints":13494},{"name":"Sundanese","code":"su","accuracy":0.18181818181818182,"datapoints":11},{"name":"Swedish","code":"sv","accuracy":0.9886773875943551,"datapoints":12188},{"name":"Tamil","code":"ta","accuracy":1,"datapoints":205},{"name":"Telugu","code":"te","accuracy":1,"datapoints":102},{"name":"Tajik","code":"tg","accuracy":0.9666666666666667,"datapoints":30},{"name":"Thai","code":"th","accuracy":1,"datapoints":572},{"name":"Turkmen","code":"tk","accuracy":0.5710519377801213,"datapoints":3793},{"name":"Tagalog","code":"tl","accuracy":0.9737223456670853,"datapoints":10351},{"name":"Turkish","code":"tr","accuracy":0.9995983734123199,"datapoints":19919},{"name":"Tatar","code":"tt","accuracy":0.9680851063829787,"datapoints":8178},{"name":"Uyghur","code":"ug","accuracy":0.9991874322860238,"datapoints":3692},{"name":"Ukrainian","code":"uk","accuracy":0.9963598179908996,"datapoints":14285},{"name":"Urdu","code":"ur","accuracy":0.9906542056074766,"datapoints":963},{"name":"Vietnamese","code":"vi","accuracy":0.9996153846153846,"datapoints":13000},{"name":"VolapΓΌk","code":"vo","accuracy":0.8511166253101737,"datapoints":806},{"name":"Walloon","code":"wa","accuracy":0.3125,"datapoints":16},{"name":"Yoruba","code":"yo","accuracy":0.6,"datapoints":5},{"name":"Chinese","code":"zh","accuracy":1,"datapoints":568},{"name":"Yiddish","code":"yi"},{"name":"Uzbek","code":"uz"},{"name":"Swahili","code":"sw"},{"name":"Albanian","code":"sq"},{"name":"Sindhi","code":"sd"},{"name":"Sardinian","code":"sc"},{"name":"Quechua","code":"qu"},{"name":"Pashto","code":"ps"},{"name":"Oriya","code":"or"},{"name":"Norwegian","code":"no"},{"name":"Nepali","code":"ne"},{"name":"Malay","code":"ms"},{"name":"Mongolian","code":"mn"},{"name":"Malagasy","code":"mg"},{"name":"Komi","code":"kv"},{"name":"Kurdish","code":"ku"},{"name":"GuaranΓ","code":"gn"},{"name":"Persian","code":"fa"},{"name":"Bihari","code":"bh"},{"name":"Azerbaijani","code":"az"},{"name":"Avaric","code":"av"},{"code":"als"},{"code":"arz"},{"code":"ast"},{"code":"azb"},{"code":"bar"},{"code":"bcl"},{"code":"bpy"},{"code":"bxr"},{"code":"cbk"},{"code":"ceb"},{"code":"ckb"},{"code":"diq"},{"code":"dsb"},{"code":"dty"},{"code":"eml"},{"code":"frr"},{"code":"gom"},{"code":"hif"},{"code":"hsb"},{"code":"ilo"},{"code":"jbo"},{"code":"krc"},{"code":"lez"},{"code":"lmo"},{"code":"lrc"},{"code":"mai"},{"code":"mhr"},{"code":"min"},{"code":"mrj"},{"code":"mwl"},{"code":"myv"},{"code":"mzn"},{"code":"nah"},{"code":"nap"},{"code":"nds"},{"code":"new"},{"code":"pam"},{"code":"pfl"},{"code":"pms"},{"code":"pnb"},{"code":"rue"},{"code":"sah"},{"code":"scn"},{"code":"sco"},{"code":"sh"},{"code":"tyv"},{"code":"vec"},{"code":"vep"},{"code":"vls"},{"code":"war"},{"code":"wuu"},{"code":"xal"},{"code":"xmf"},{"code":"yue"}]
curl --location --request GET 'https://zylalabs.com/api/4484/multilingual+language+recognition+api/5504/languages+available' --header 'Authorization: Bearer YOUR_API_KEY'
To use this endpoint you must indicate a text and if you want to obtain a prediction about the detected language (true or false).
Language detection - Endpoint Features
Object | Description |
---|---|
Request Body |
[Required] Json |
{"lang":"en","prob":0.9216727018356323,"confidence":0.9123906549066305,"isReliable":true,"highAccuracyLanguage":true}
curl --location --request POST 'https://zylalabs.com/api/4484/multilingual+language+recognition+api/5505/language+detection' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"text": "Today is a great day",
"includePredictions": false
}'
Header | Description |
---|---|
Authorization
|
[Required] Should be Bearer access_key . See "Your API Access Key" above when you are subscribed. |
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To use this API, users must indicate a text to identify the language.
The Multilingual Language Recognition API designed to automatically identify and classify the language of a given text or character string.
There are different plans to suit all tastes, including a free trial for a small number of requests, but your rate is limited to avoid abuse of the service.
Zyla provides a wide range of integration methods for almost all programming languages. You can use these codes to integrate with your project as you need.
A Multilingual Language Recognition API is crucial, as it facilitates automatic language detection for users, simplifying the process of identifying the language in which a given text is written.
The "GET Languages available" endpoint returns a list of languages that can be detected, including their names, codes, accuracy rates, and data points. The "POST Language detection" endpoint returns the detected language, probability, confidence level, and reliability of the prediction.
Key fields in the "GET Languages available" response include "name" (language name), "code" (language code), "accuracy" (detection accuracy), and "datapoints" (number of data points used). In the "POST Language detection" response, key fields are "lang" (detected language), "prob" (probability), "confidence" (confidence level), and "isReliable" (reliability status).
The response data is organized in JSON format. The "GET Languages available" endpoint returns an array of language objects, while the "POST Language detection" endpoint returns a single object with language detection results.
The "POST Language detection" endpoint requires a "text" parameter for the input text and an optional "predict" parameter to specify if a prediction about the detected language is needed (true or false).
Users can customize requests by providing different text inputs to the "POST Language detection" endpoint. For the "GET Languages available" endpoint, no parameters are needed, as it returns all supported languages.
Typical use cases include social media monitoring for sentiment analysis, customer service for routing messages, multilingual website content delivery, text translation pre-processing, and content moderation to filter comments.
Data accuracy is maintained through advanced algorithms and machine learning techniques that analyze linguistic patterns. The API's performance is continuously improved by training on diverse datasets, ensuring reliable language detection.
Users can expect consistent data patterns in the responses, such as high accuracy rates for widely spoken languages and varying accuracy for less common languages. The "confidence" field helps gauge the reliability of the detection.
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