L Language Translator

[Ara Kistner]

Inour free version we use Phrase Based Machine Translations provided by Google Translate, while in our paid versions use Google Translate Neural Translations which are very accurate for popular language pairs.

In the paid versions you can refine the automatic translations yourself or order professional translations or proofreading of a translated content.

You can get a translation cost estimate by using our Website Translation Cost Calculator

Yes, we use Google Translate widget for website which provides free phrase based machine translations, which makes it possible to make your wordpress website multilingual instantly upon installation.

In our paid versions we use Google Translate state of the art Neural Translations which are included in the service price and there are no limits on the word count.

By the way, we can help you to translate your website with a cost effective approach by post-editing your automatic translated content.

The proofreading service will be done by a native speakers and if you want to take the quality to another service, we also have a professional website translation service available.

You can get an instant website translation estimate by using our Website Word Counter tool.

Multilingual SEO is a SEO strategy which uses new content generation technique by translating your original content and making your website multilingual. By translating your website into many languages you are creating many new multilingual keywords targeted for international market. It helps to increase your search appearnce on search engines results pages (SERPs), which can generate more traffic, increase sales and rise the conversion rate.

In our free version we provide Phrase Based machine translations from Google Translate. While in our paid versions we provide you state of the art Neural Translations from Google Translate. We also do not have limits on the number of words on your website unlike other translate plugins.

By the way we alse offer a cost effective approach for improving the website translations. You can get a automatic translation post-editing service from us, which will be done by a native speaker or order a professional translation. You can get an instant estimate for your website on Website Translation Quote

You need to go to the language you want to edit, for instance, French: and add ?language_edit=1 to the end of the URL: _edit=1 and you will see the Edit buttons near each text. Read more at How to edit translations?

If you want us to translate your website professionally or provide you a proofreading service for automatic translated content, you can get an instant estimate from Website Translation Quote, where you will get a detailed document with the list of pages, unique word count and prices to translate them.

The Language Translator plugin was recently released. It allows you to translate selected text into the desired language. This is based on a free instance of Azure Translator. (Please do not abuse it)

All Watson services use Secure Sockets Layer (SSL) (or Transport Layer Security (TLS)) for secure connections between the client and server. The connection is verified against the local certificate store to ensure authentication, integrity, and confidentiality.

You can pass either a bearer token in an authorization header or an API key. Tokens support authenticated requests without embedding service credentials in every call. API keys use basic authentication. For more information, see Authenticating to Watson services.

Language Translator uses standard HTTP response codes to indicate whether a method completed successfully. HTTP response codes in the 2xx range indicate success. A response in the 4xx range is some sort of failure, and a response in the 5xx range usually indicates an internal system error that cannot be resolved by the user. Response codes are listed with the method.

Data collection is disabled for the Language Translator service. Regardless of whether you set the X-Watson-Learning-Opt-Out request header, the service does not log or retain data from requests and responses.

IBM is announcing the deprecation of the Watson Language Translator service for IBM Cloud in all regions. As of 10 June 2023, the Language Translator tile will be removed from the IBM Cloud Platform for new customers; only existing customers will be able to access the product. As of 10 June 2024, the service will reach its End of Support date. As of 10 December 2024, the service will be withdrawn entirely and will no longer be available to any customers.: deprecated

A score between 0 and 1 indicating the confidence of source language detection. A higher value indicates greater confidence. This is returned only when the service automatically detects the source language.

The model to use for translation. For example, en-de selects the IBM-provided base model for English-to-German translation. A model ID overrides the source and target parameters and is required if you use a custom model. If no model ID is specified, you must specify at least a target language.

Language code that specifies the language of the input text. If omitted, the service derives the source language from the input text. The input must contain sufficient text for the service to identify the language reliably.

If the default parameter isn't specified, the service returns all models (default and non-default) for each language pair. To return only default models, set this parameter to true. To return only non-default models, set this parameter to false. There is exactly one default model, the IBM-provided base model, per language pair.

Depending on the type of customization and the size of the uploaded files, training time can range from minutes for a glossary to several hours for a large parallel corpus. To create a model that is customized with a parallel corpus and a forced glossary, customize the model with a parallel corpus first and then customize the resulting model with a forced glossary.

You can create a maximum of 10 custom models per language pair. For more information about customizing a translation model, including the formatting and character restrictions for data files, see Customizing your model.

The ID of the translation model to use as the base for customization. To see available models and IDs, use the List models method. Most models that are provided with the service are customizable. In addition, all models that you create with parallel corpora customization can be further customized with a forced glossary.

A file with forced glossary terms for the source and target languages. The customizations in the file completely overwrite the domain translation data, including high frequency or high confidence phrase translations.

You can upload only one glossary file for a custom model, and the glossary can have a maximum size of 10 MB. A forced glossary must contain single words or short phrases. For more information, see Supported file formats in the method description.

A file with parallel sentences for the source and target languages. You can upload multiple parallel corpus files in one request by repeating the parameter. All uploaded parallel corpus files combined must contain at least 5000 parallel sentences to train successfully. You can provide a maximum of 500,000 parallel sentences across all corpora.

A single entry in a corpus file can contain a maximum of 80 words. All corpora files for a custom model can have a cumulative maximum size of 250 MB. For more information, see Supported file formats in the method description.

Language code that specifies the language of the source document. If omitted, the service derives the source language from the input text. The input must contain sufficient text for the service to identify the language reliably.

Lists all supported languages for translation. The method returns an array of supported languages with information about each language. Languages are listed in alphabetical order by language code (for example, af, ar). In addition to basic information about each language, the response indicates whether the language is supported_as_source for translation and supported_as_target for translation. It also lists whether the language is identifiable.

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