Customize Amazon Translate output to meet your domain and organization specific vocabulary

Amazon Translate is a neural device translation service that provides quickly, top quality, cost effective, and personalized language translation. When you translate from one language to another, you want your maker translation to be precise, fluent, and most importantly contextual. Modification is type in keeping your device translation contextual. Amazon Translate offers several capabilities for customization to accomplish the finest device translation. One such ability is custom terms. Customized terms enables you to personalize your translation output such that your domain and company particular vocabulary such as brand names, character names, design names, and other unique material (named entities) are translated exactly the way you require. To use the customized terminology feature, you develop a terms using a terms file in a CSV or TMX file format and define this custom terminology as a criterion in an Amazon Translate real-time translation or asynchronous batch processing demand.
Amazon Translate now supports multi-directional customized terms. You no longer have to create multiple terms CSV files with each one differing just in the very first column to suggest the source language, consist of extra preprocessing logic to determine the dominant language, and pick the right terminology declare the translation demand. You can now utilize a single custom terminology for numerous source and target language combinations. Even when you set the source language to be identified immediately, Amazon Translate utilizes Amazon Comprehend to figure out the dominant language of the source product, utilizes it as the source language, and translates the text utilizing the terms defined in the custom terminology. For additional information on custom-made terminology, describe Customizing Your Translations with Custom Terminology.
In this post, we walk you through the step-by-step process of how to utilize custom terms and get a tailored machine translated output safely.
Service introduction
To tailor your translation for terms that are distinct to your market domain or organization, you define these terms in a terms file in CSV or TMX file format. The terms within the customized terms are thought about case-sensitive, and Amazon Translate recognizes a precise match between a terminology entry and a string in the source text when their case matches.
For our use case, we have our information in CSV format, and the name of the file is custom_terminology. csv. The data in the file need to likewise be UTF-8 encoded. The following table summarizes the contents of the file.

Alexa
Alexa
Alexa
Alexa
Alexa

en
es
fr
hi
ta

AZ2
AZ2
AZ2
AZ2
AZ2

Echo
Echo
Echo
Echo
Echo

Amazon
Amazon
Amazon
Amazon
Amazon

Program
Program
Show
Show
Show

Import terminology
We import our multi-directional customized terms using the custom_terminology. csv file. In the following areas, we reveal you how to import your terminology through the AWS Management Console, AWS Command Line Interface (AWS CLI), or with the Amazon Translate SDK (Python Boto3).
Amazon Translate console
To import the terminology through the console, complete the following actions:

Your custom-made terms is now listed on the Custom terminology page.

Your data is always safe with Amazon Translate. Its encrypted using an AWS owned encryption secret using AWS Key Management Service (AWS KMS) by default. You can encrypt it utilizing a secret from your bank account or use a secret from a various account.

For Name, enter a proper name, for instance CustomTerminologyDemo.
For Terminology file, submit the custom_terminology. csv file.
For Terminology file data format, select CSV, considering that we published a CSV file.
For Directionality, choose Multi-directional.
For Encryption secret, for the function of this post, we leave it as default, an AWS owned and managed secret. You can select any appropriate key.

On the Amazon Translate console, in the navigation pane, select Custom terms.
Choose Create terminology.

Select Create Terminology.

AWS CLI
The following AWS CLI commands are formatted for Unix, Linux, and macOS. For Windows, replace the backslash () Unix continuation character at the end of each line with a caret (^).
You can call the import-terminology AWS CLI command to produce a custom-made terms resource:

Words like Amazon, Echo, Show, AZ2, and Alexa have been translated into Devanagari script.
Lets carry out the exact same translation utilizing our multi-directional custom terminology.

You can utilize the list-terminologies command to note all the custom-made terms created:.

Amazon Translate SDK (Python Boto3).
The following Python 3 code creates a customized terminology, notes all the customized terminology, and uses the terminology resource part of the real-time translation call:.

To utilize the custom terminology function, you develop a terminology using a terms file in a CSV or TMX file format and specify this customized terms as a specification in an Amazon Translate real-time translation or asynchronous batch processing request.
You no longer have to produce several terminology CSV submits with each one differing just in the first column to show the source language, consist of extra preprocessing logic to recognize the dominant language, and select the appropriate terms file for the translation request. Even when you set the source language to be detected immediately, Amazon Translate utilizes Amazon Comprehend to identify the dominant language of the source material, uses it as the source language, and translates the text using the terms defined in the customized terms. For additional details on customized terms, refer to Customizing Your Translations with Custom Terminology.
In addition, with multi-directional custom-made terminology, the management overhead of maintaining multiple terms is dramatically reduced, and you can utilize a single terms to translate to and from a specific language.

result = translate.translate _ text(.
Text= SOURCE_TEXT,.
TerminologyNames= [ CustomTerminology_boto3],.
SourceLanguageCode= automobile,
TargetLanguageCode= OUTPUT_LANG_CODE.
).

OUTPUT_LANG_CODE=en.

The response appears like the following:.

aws equate get-terminology– name CustomTerminologyDemo— region us-east-1.

The following screenshot reveals the equated text.

The following screenshot shows the translated text with customized terminology used.

You can utilize the get-terminology command to get the details of a particular custom terms resource:.

print(” Translated Text: “. format( outcome [ TranslatedText]).

with open( custom_terminology. csv, rb) as ct_file:.
translate.import _ terminology(.
Name= CustomTerminology_boto3,
MergeStrategy= OVERWRITE,
Description= Terminology for Demo through boto3,.
TerminologyData=
File: ct_file. read(),.
Format: CSV.
Directionality: MULTI.
).

To erase a customized terminology resource, you can utilize the delete-terminology command:.

” TerminologyProperties”: LATEST”,.
” Format”: “CSV”,.
” Directionality”: “MULTI”.
” SourceLanguageCode”: “en”,.
” TargetLanguageCodes”: [” hi”,.
” fr”,.
” ta”,.
” es”.
],.
” SizeBytes”: 136,.
” TermCount”: 20,.
” CreatedAt”: “2021-10-12T15:29:51.294000 -04:00″,.
” LastUpdatedAt”: “2021-10-12T15:29:51.458000 -04:00″.
,.
” TerminologyDataLocation”: 123456789012

Real-time translation utilizing multi-directional customized terms.
In this section, we show 2 use cases using multi-directional custom-made terminology for real-time translation in Amazon Translate.
Scenario 1: Multi-directional custom-made terminology.
For a fundamental presentation of using multi-directional custom terms with real-time translation, we use the following sample text in Spanish to be equated to French.
Amazon ha presentado hoy el Echo Show 15, una nueva incorporación a la familia Echo Show que está diseñada para ser el corazón digital de tu hogar. Con una pantalla Full HD de 15,6 pulgadas y 1080p, el Echo Show 15 puede fijarse en la pared o colocarse sobre un soporte compatible, ya sea en orientación vertical u horizontal, y está diseñado para ayudarte a mantenerte organizado, conectado y entretenido. El Echo Show 15 está fabricado con el procesador Amazon AZ2 Neural Edge de última generación, una pantalla de inicio rediseñada con más opciones de personalización, nuevas funcionalidades de personalización con ID Visual, y experiencias de Alexa totalmente nuevas.
On the Amazon Translate console, complete the following steps:.

Choose Source language as Auto (vehicle).

response = translate.get _ terms(.
Name= CustomTerminology_boto3,
TerminologyDataFormat= CSV
).
print(” Name: “. format( reaction [” TerminologyProperties”] [” Name”]).
print(” Description: “. format( response [” TerminologyProperties”] [” Description”]).
print(” ARN: “. format( response [” TerminologyProperties”] [” Arn”]).
print(” Directionality: “. format( response [” TerminologyProperties”] [” Directionality”]).

action = translate.list _ terminologies().
print( str( terminology_names)).

About the Authors.
Siva Rajamani is a Boston-based Enterprise Solutions Architect at AWS. He delights in working carefully with consumers and supporting their digital improvement and AWS adoption journey. His core locations of focus are serverless, application combination, and security. Beyond work, he delights in outdoors activities and viewing documentaries.
Sudhanshu Malhotra is a Boston-based Enterprise Solutions Architect for AWS. His core areas of focus are DevOps, device learning, and security.
Watson G. Srivathsan is the Sr. Item Manager for Amazon Translate, AWSs natural language processing service. On weekends you will find him exploring the outdoors in the Pacific Northwest.

translate = boto3.client( equate).

aws translate get-terminology– name CustomTerminologyDemo– terminology-data-format CSV– area us-east-1.

Choose Source language as Auto (vehicle).

The reaction appears like the following:.

In the Additional settings section, turn Custom terms.

Running the Python code prints the following result:.

aws equate delete-terminology– name CustomTerminologyDemo– region us-east-1.

Enter the provided text in the Source Language text location.

Choose Spanish (es) as the Source language.
Select French (fr) as the Target Language.
In the Additional settings area, turn Custom terminology.

Select CustomTerminologyDemo as the terms.
Go into the supplied text in the Source Language text location.

The source language was immediately found as French, and with the multi-directional custom terminology assistance, Amazon Translate was able to use the provided terms file to customize the translation and maintain the Latin script for words like Amazon, Echo, Show, AZ2, and Alexa.
Conclusion.
When you utilize custom-made terminology with translation demands, you can ensure that your special material, such as brand name names, character names, and design names, is translated precisely the way you need it, no matter context and the Amazon Translate algorithms decision. In addition, with multi-directional custom terminology, the management overhead of keeping numerous terminologies is dramatically minimized, and you can utilize a single terms to equate to and from a particular language. For more details about how to get the best translation quality when utilizing custom terminology, see Best Practices.

python translate_custom_terminology. py.

Translated Text: Amazon today introduced Echo Show 15, a brand-new addition to the Echo Show family that is developed to be the digital heart of your house.

aws translate import-terminology
— description “Multi-Directional custom terminology in AWS Translate”
— data-file fileb:// custom_terminology. csv.
— merge-strategy OVERWRITE
— name CustomTerminologyDemo
— area us-east-1
— terminology-data Format= CSV, Directionality= MULTI.

[ CustomTerminology_boto3] Call: CustomTerminology_boto3.
Description: Terminology for Demo through boto3.
ARN: arn: aws: translate: us-east-1:123456789012: terminology/CustomTerminology _ boto3/LATEST.
Directionality: MULTI.

You get a response like the following snippet:.

import boto3.
import json.

Pick Hindi (hi) as the Target Language.

The following screenshot shows the translated text with custom-made terminology applied.

SOURCE_TEXT = (” Amazon a présenté aujourd hui Echo Show 15, un nouvel ajout à la famille Echo Show qui est conçu put être le cœur numérique de votre maison”).

Spanish wasnt the very first column in the terminology file we published, however with multi-directional terminology assistance, Amazon Translate had the ability to use the supplied terminology file to tailor the translation.
Situation 2: Automatically find source language.
In this usage case, we demonstrate the capability in Amazon Translate to automatically discover the source language and use the supplied terms file to personalize the translation. We use the following sample text in French and equate it to Hindi:.
Aujourd hui, Amazon présente Echo Show 15, dernier-né de la gamme Echo Show, imaginé pour être le cœur numérique de votre domicile. Avec un écran Full HD 1080p de 15,6″, Echo Show 15 peut être fixé au mur ou posé sur un assistance compatible, en orientation portrait ou paysage, et est conçu pour vous aider à rester organisé · e, connecté · e et diverti · e. Echo Show 15 est équipé du processeur Amazon AZ2 Neural Edge de nouvelle génération, dun écran daccueil repensé avec plus doptions et de nouvelles fonctionnalités de personnalisation grâce à lidentifiant facial, et bénéficie de toutes nouvelles expériences Alexa.
First lets show the translation without custom-made terminology.

Pick CustomTerminologyDemo as the terms.
Go into the supplied sample text in the Source Language text location.

Pick Hindi (hi) as the Target Language.

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