시작
Kore.ai 대화형 플랫폼
챗봇 개요
자연어 처리(NLP)
봇 개념 및 용어들
빠른 시작 가이드
봇 빌더 접근 방법
사용 고지 사항 (영어)
Kore.ai 봇 빌더로 작업하기
봇 구축 시작하기
릴리스 정보
현재 버전 (영어)
이전 버전 (영어)

개념
디자인
스토리보드
대화 작업
개요
Using the Dialog Builder Tool
노드 유형
사용자 의도 노드
대화 노드
엔티티 노드
양식 노드
확인 노드
서비스 노드
봇 조치 노드
Service Node
WebHook 노드
스크립트 노드
노드 그룹화하기
Agent Transfer Node
사용자 프롬프트
음성 통화 속성
대화 관리
노드 및 전환
구성 요소 전환
컨텍스트 개체
이벤트 기반 봇 조치
지식 그래프
소개
지식 추출
지식 그래프 생성
봇에 지식 그래프 추가
그래프 생성
지식 그래프 작성
FAQ 추가
작업 실행
기존 소스에서 FAQ 구축
특성, 동의어 및 불용어
변수 네임스페이스 관리
수정
용어 편집 및 삭제
용어 편집 및 삭제
질문과 응답 편집
Knowledge Graph Training
지식 그래프 분석
봇 온톨로지 가져오기 및 내보내기
지식 그래프 가져오기
지식 그래프 내보내기
지식 그래프 생성
CSV 파일에서
JSON 파일
지식 그래프 생성
경고 작업
스몰 토크
Digital Skills
디지털 양식
Views
Digital Views
Panels
Widgets
기차
봇 성능 향상 – NLP 최적화
기계 학습
소개
모델 검증
기초 의미
지식 그래프 학습
특성
순위 및 해결
고급 NLP 설정
NLP 설정 및 지침
봇 인텔리전스
소개
컨텍스트 관리
컨텍스트 관리
대화 관리
다중 – 의도 탐지
엔티티 수정
기본 대화
정서 관리
어조 분석
Test & Debug
봇과 대화
발화 테스트
배치 테스트하기
대화 테스트
배포
채널 활성화
봇 게시
분석
봇 분석하기
Conversations Dashboard
Performance Dashboard
사용자 정의 대시보드
소개
맞춤형 메타 태그
사용자 정의 대시보드 생성 방법
Conversation Flows
NLP 지표
Containment Metrics
사용량 지표
스마트 봇
소개
범용 봇
소개
범용 봇 정의
범용 봇 생성
범용 봇 학습
범용 봇 커스터마이징
범용 봇용 추가 언어 활성화
스토어
Manage Assistant
플랜 및 사용량
Overview
Usage Plans
Support Plans
플랜 관리
봇 인증
다국어 봇
개인 식별 정보 삭제하기
봇 변수 사용
IVR 통합
일반 설정
봇 관리

방법
간단한 봇 생성하기
Design Conversation Skills
뱅킹 봇 생성
뱅킹 봇 – 자금 이체
뱅킹 봇 – 잔액 업데이트
Knowledge Graph (KG) 구축
스마트 경고를 예약하는 방법
Design Digital Skills
디지털 양식 설정 방법
디지털 보기 설정 방법
데이터 테이블에 데이터를 추가하는 방법
데이터 테이블 내 데이터 업데이트 방법
UI 양식에서 데이터 테이블에 데이터를 추가하는 방법
Train the Assistant
특성 사용 방법
의도와 엔티티에 대한 패턴 사용 방법
컨텍스트 전환 관리 방법
Deploy the Assistant
상담사 전환을 설정하는 방법
봇 기능 사용 방법
콘텐츠 변수 사용 방법
전역 변수 사용 방법
Kore.ai 웹 SDK 튜토리얼
Kore.ai 위젯 SDK 튜토리얼
Analyze the Assistant
사용자 정의 대시보드 생성 방법
사용자 지정 태그를 사용하여 봇 메트릭을 필터링하는 방법

API 및 SDK
API 참조
Kore.ai API 사용
API 목록
API 컬렉션
koreUtil Libraries
SDK 참조
상담사 전환을 설정하는 방법
봇 기능 사용 방법
콘텐츠 변수 사용 방법
전역 변수 사용 방법
소개
Kore.ai 웹 SDK 튜토리얼
Kore.ai 위젯 SDK 튜토리얼

관리
소개
봇 관리자 콘솔
대시보드
사용자 관리
사용자 관리
그룹 관리
역할 관리
봇 관리 모듈
등록
사용자 초대
사용자 등록을 위한 대량 초대 보내기
사용자 및 사용자 데이터 가져오기
Active Directory에서 사용자 동기화
보안 및 준수
싱글 사인 온 사용
보안 설정
Kore.ai 커넥터
봇 관리자용 분석
Billing (지원하지 않음)
  1. Docs
  2. Virtual Assistants
  3. Advanced Topics
  4. Language Management
  5. Managing Translation Services

Managing Translation Services

The Kore.ai XO Platform offers multiple ways to train your virtual assistant for language understanding. One of the ways is to use translation services to translate the user input. In this approach, you can train the virtual assistant in a language (NLU Language) other than the interaction language. For example, you can enable Spanish as an interaction language but train the assistant using English language training data.

Translation services can also be used for translating the bot responses if they are defined in a language other than the conversation language. The Platform allows you to define language-specific responses for each of the languages enabled for the assistant. However, you may choose to write responses in a language other than the enabled language.

The Platform provides out-of-the-box support for Microsoft Translator and Google Translation APIs. You can also use the Custom Translation Engine feature to integrate with any other translation services or your in-house translation services.

Configuring Microsoft Translator Service

To enable automatic translation using Microsoft Translation Services, please follow the steps below:

  1. Go to Build > Configurations > Languages > Translation Configurations.
  2. Select Microsoft Translator.
  3. Provide the API Key of your Microsoft Translator API service. Learn More.
  4. Click Save to complete the setup.

Configuring Google Translation Service

To enable automatic translation using Google Translation Services, please follow the steps below: 

  1. Go to Build > Configurations > Languages > Translation Configurations.
  2. Select Google Translator.
  3. Provide the API Key (Eg: AIzaXXXXXXXXXXXXXXXXXXXEpeW4xa0) of your Google Translation API service in the Access Key field. Learn More.
    • Note that the Platform does not validate the key. It is highly recommended that the key is validated beforehand and is active and working. A tool like Postman can be used to validate the key.

    • You can also save the translator key in an environment / content variable and provide that variable name enclosed in double curly braces while setting up the configuration.

  4. Click Save to complete the setup.

To know how to use the service, please visit KoreUtil Libraries – autoTranslate.

Configuring Custom Translation Service

The Custom Translation Service allows you to use translation services by integrating with other translation providers or to integrate with any in-house translation services you may have.

How it works

Here is how custom translation services work:

  1. Follow the instructions below to enable the Custom Translation Engine feature.
  2. You can set up the integration with your translation service APIs using the Get or Post method.
  3. Refer to your translation service documentation for the authentication mechanism, request payload, and response payload.
  4. This integration is used for translating both the user input as well as the bot responses. The platform will automatically make the following information available in the context during runtime.
  5. It will make use of the following functions while defining the request payload.
    1. koreUtil.conversation.sourceText()– This function will return the text to be translated.
      1. If the user’s input is being translated, then the function will return the user’s input.
      2. If the bot response is being translated, then the function will return the bot response.
    2. For translating user input, this function will return the user input. For translating the bot response, the function will return the bot response text.
    3. koreUtil.conversation.getSourceLanguage() – This function returns the current language of the text to be translated.
      1. If the user input is being translated, then the function will return the language in which the user is interacting.
      2. If the bot response is being translated, then the function will return the language in which the response is written.
    4. koreUtil.conversation.getTargetLanguage() – This function returns the language to which the text should be translated to.
      1. If the user input is being translated, then the function will return the language to which the input should be translated.
      2. If the bot response is being translated, then the function will return the language to which the response should be translated.The platform invokes the translation service using the defined configurations.
  6. The translation engine should share the translated text as part of the API response.
  7. Map the relevant field from the response payload to be used as the translated text.

Enabling a Custom Translation Engine

  1. Go to Build > Configurations > Languages > Translation Configurations.
  2. Select Custom, and choose Add Custom Engine from the dropdown.

  3. Provide a name for the Custom Translation Engine.
  4. Define the request payload for sending the text to be translated. Refer to the details provided above for defining the request payload.
  5. Refer to the Service Node documentation to learn more about how to configure service integrations.

  6. After defining the request payload, you can test the integration by providing the required details from the Test Request tab. Provide the sample values for the variables shown under the Sample Context Values sections, click Test to verify if the custom translation connection is established.

  7. After a successful test, the platform displays the API response received from the translation service.
  8. Verify the response payload and map the translated text from the payload in the Translated Output field.

  9. Click the Extract button to verify if the translation output is correctly mapped.

  10. Click Save & Exit to return to the Languages page.
  11. Click Save to complete the configuration.

Managing Translation Services

The Kore.ai XO Platform offers multiple ways to train your virtual assistant for language understanding. One of the ways is to use translation services to translate the user input. In this approach, you can train the virtual assistant in a language (NLU Language) other than the interaction language. For example, you can enable Spanish as an interaction language but train the assistant using English language training data.

Translation services can also be used for translating the bot responses if they are defined in a language other than the conversation language. The Platform allows you to define language-specific responses for each of the languages enabled for the assistant. However, you may choose to write responses in a language other than the enabled language.

The Platform provides out-of-the-box support for Microsoft Translator and Google Translation APIs. You can also use the Custom Translation Engine feature to integrate with any other translation services or your in-house translation services.

Configuring Microsoft Translator Service

To enable automatic translation using Microsoft Translation Services, please follow the steps below:

  1. Go to Build > Configurations > Languages > Translation Configurations.
  2. Select Microsoft Translator.
  3. Provide the API Key of your Microsoft Translator API service. Learn More.
  4. Click Save to complete the setup.

Configuring Google Translation Service

To enable automatic translation using Google Translation Services, please follow the steps below: 

  1. Go to Build > Configurations > Languages > Translation Configurations.
  2. Select Google Translator.
  3. Provide the API Key (Eg: AIzaXXXXXXXXXXXXXXXXXXXEpeW4xa0) of your Google Translation API service in the Access Key field. Learn More.
    • Note that the Platform does not validate the key. It is highly recommended that the key is validated beforehand and is active and working. A tool like Postman can be used to validate the key.

    • You can also save the translator key in an environment / content variable and provide that variable name enclosed in double curly braces while setting up the configuration.

  4. Click Save to complete the setup.

To know how to use the service, please visit KoreUtil Libraries – autoTranslate.

Configuring Custom Translation Service

The Custom Translation Service allows you to use translation services by integrating with other translation providers or to integrate with any in-house translation services you may have.

How it works

Here is how custom translation services work:

  1. Follow the instructions below to enable the Custom Translation Engine feature.
  2. You can set up the integration with your translation service APIs using the Get or Post method.
  3. Refer to your translation service documentation for the authentication mechanism, request payload, and response payload.
  4. This integration is used for translating both the user input as well as the bot responses. The platform will automatically make the following information available in the context during runtime.
  5. It will make use of the following functions while defining the request payload.
    1. koreUtil.conversation.sourceText()– This function will return the text to be translated.
      1. If the user’s input is being translated, then the function will return the user’s input.
      2. If the bot response is being translated, then the function will return the bot response.
    2. For translating user input, this function will return the user input. For translating the bot response, the function will return the bot response text.
    3. koreUtil.conversation.getSourceLanguage() – This function returns the current language of the text to be translated.
      1. If the user input is being translated, then the function will return the language in which the user is interacting.
      2. If the bot response is being translated, then the function will return the language in which the response is written.
    4. koreUtil.conversation.getTargetLanguage() – This function returns the language to which the text should be translated to.
      1. If the user input is being translated, then the function will return the language to which the input should be translated.
      2. If the bot response is being translated, then the function will return the language to which the response should be translated.The platform invokes the translation service using the defined configurations.
  6. The translation engine should share the translated text as part of the API response.
  7. Map the relevant field from the response payload to be used as the translated text.

Enabling a Custom Translation Engine

  1. Go to Build > Configurations > Languages > Translation Configurations.
  2. Select Custom, and choose Add Custom Engine from the dropdown.

  3. Provide a name for the Custom Translation Engine.
  4. Define the request payload for sending the text to be translated. Refer to the details provided above for defining the request payload.
  5. Refer to the Service Node documentation to learn more about how to configure service integrations.

  6. After defining the request payload, you can test the integration by providing the required details from the Test Request tab. Provide the sample values for the variables shown under the Sample Context Values sections, click Test to verify if the custom translation connection is established.

  7. After a successful test, the platform displays the API response received from the translation service.
  8. Verify the response payload and map the translated text from the payload in the Translated Output field.

  9. Click the Extract button to verify if the translation output is correctly mapped.

  10. Click Save & Exit to return to the Languages page.
  11. Click Save to complete the configuration.
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