La API de Clasificación de Idiomas de Texto está diseñada para identificar y determinar automáticamente el idioma de un texto o cadena de caracteres dada. Utilizando algoritmos avanzados y análisis lingüístico, esta API ofrece una integración fluida en diversas aplicaciones y sistemas, proporcionando capacidades precisas y confiables de detección de idiomas.
Básicamente, la API de Clasificación de Idiomas de Texto funciona analizando los patrones estructurales y gramaticales presentes en el texto proporcionado. Utilizando modelos estadísticos y técnicas de aprendizaje automático, la API puede discernir las características únicas asociadas con diferentes idiomas, lo que le permite hacer predicciones informadas sobre el idioma en el que está escrito el texto.
Una de las principales fortalezas de la API de Clasificación de Idiomas de Texto radica en su capacidad para identificar con precisión una amplia gama de idiomas de todo el mundo. Ya sea que el texto esté escrito en un idioma hablado comúnmente, como inglés o español, o en un idioma menos utilizado, como el catalán o el bosnio. La API puede reconocer y categorizar el idioma de manera efectiva con un alto grado de precisión.
Además, la API de Clasificación de Idiomas de Texto es capaz de manejar entradas de texto de diferentes longitudes, desde oraciones cortas hasta párrafos largos. Esta flexibilidad permite a los desarrolladores integrar la funcionalidad de detección de idiomas en una amplia gama de aplicaciones, desde herramientas simples de análisis de texto hasta sistemas complejos de procesamiento de lenguaje natural.
La API también está diseñada para ser altamente escalable y soportar grandes volúmenes de entrada de texto con una latencia mínima. Esta escalabilidad la hace ideal para su implementación en entornos donde se requiere detección rápida de idiomas, como aplicaciones de chat en tiempo real, plataformas de monitoreo de redes sociales o sistemas de moderación de contenido a gran escala.
En resumen, la API de Clasificación de Idiomas de Texto te permite identificar automáticamente el idioma de un texto dado. Con su amplio soporte de idiomas y precisión, la API es adecuada para una amplia gama de aplicaciones en diversas industrias, lo que permite a los usuarios integrar fácilmente la funcionalidad de detección de idiomas en sus aplicaciones y sistemas.
Recibirá parámetros y le proporcionará un JSON.
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Para utilizar este punto final, solo tienes que ejecutarlo y recibirás los idiomas disponibles para detectar.
[{"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":"Volapük","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":"Guaraní","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/3547/text+language+classifier+api/3893/languages+available' --header 'Authorization: Bearer YOUR_API_KEY'
Para utilizar este punto final, debes indicar un texto y si deseas obtener una predicción sobre el idioma detectado (verdadero o falso).
Detección de idiomas. - Características del Endpoint
| Objeto | Descripción |
|---|---|
Cuerpo de la Solicitud |
[Requerido] Json |
{"lang":"en","prob":0.9854544401168823,"confidence":0.983413940295577,"isReliable":true,"highAccuracyLanguage":true}
curl --location --request POST 'https://zylalabs.com/api/3547/text+language+classifier+api/3894/language+detection' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"text": "This is my house",
"includePredictions": false
}'
| Encabezado | Descripción |
|---|---|
Autorización
|
[Requerido] Debería ser Bearer access_key. Consulta "Tu Clave de Acceso a la API" arriba cuando estés suscrito. |
Sin compromiso a largo plazo. Mejora, reduce o cancela en cualquier momento. La Prueba Gratuita incluye hasta 50 solicitudes.
Para utilizar esta API, los usuarios deben indicar un texto para identificar el idioma.
La API del Clasificador de Lenguaje de Texto está diseñada para identificar y clasificar automáticamente el idioma de un texto o cadena de caracteres dada.
Hay diferentes planes para todos los gustos, incluyendo una prueba gratuita para un pequeño número de solicitudes, pero su tarifa está limitada para evitar el abuso del servicio.
Zyla proporciona una amplia gama de métodos de integración para casi todos los lenguajes de programación. Puedes utilizar estos códigos para integrarte con tu proyecto según lo necesites.
El endpoint "GET Idiomas disponibles" devuelve una lista de idiomas que pueden ser detectados, incluyendo sus nombres, códigos, precisión y puntos de datos. El endpoint "POST Detección de idioma" devuelve el idioma detectado, la probabilidad, el nivel de confianza y la fiabilidad de la predicción.
Para el endpoint "GET Idiomas disponibles", los campos clave incluyen "nombre", "código", "exactitud" y "puntos de datos". Para el endpoint "POST Detección de idioma", los campos clave son "idioma", "prob", "confianza", "esConfiable" y "idiomaDeAltaExactitud".
Los datos de respuesta están estructurados en formato JSON. El endpoint "GET Idiomas disponibles" devuelve un arreglo de objetos de idioma, mientras que el endpoint "POST Detección de idiomas" devuelve un único objeto con los resultados de la detección de idiomas.
El endpoint "Detección de idioma POST" requiere un parámetro de texto para la identificación del idioma y un parámetro booleano opcional para solicitar una verificación de la fiabilidad de la predicción. El endpoint "Obtener idiomas disponibles" no requiere ningún parámetro.
La precisión de los datos se mantiene a través de algoritmos avanzados y análisis lingüístico, utilizando modelos estadísticos y técnicas de aprendizaje automático. Las actualizaciones continuas y el entrenamiento en conjuntos de datos diversos ayudan a mejorar las capacidades de detección.
Los casos de uso típicos incluyen la monitorización de redes sociales para el análisis de sentimientos, el servicio al cliente para el enrutamiento de mensajes, la entrega de contenido de sitios web multilingües, el procesamiento previo de traducciones de texto y la moderación de contenido para filtrar comentarios inapropiados.
Los usuarios pueden aprovechar los datos devueltos para mejorar la experiencia del usuario al proporcionar contenido en el idioma detectado, mejorar la eficiencia del soporte al cliente y asegurar un procesamiento de lenguaje preciso en aplicaciones como servicios de traducción.
Los usuarios pueden esperar patrones consistentes en los datos de respuesta, como alta precisión para los idiomas más hablados y precisión variable para los idiomas menos comunes. Los niveles de confianza y los indicadores de fiabilidad ayudan a evaluar la credibilidad de los resultados de detección.
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