Watson Voice Agent를 활용한 ‘한국어’ 인공지능 콜센터 제작하기: 챗봇 그 이상을 위하여 (IBM Devday 발표자료)

© 2018 IBM Corporation
맹윤호 Yunho Maeng
IBM Watson & Cloud Platform
Technical Service Professional
Watson Voice Agent를
활용한 ‘한국어’
인공지능 콜센터
제작하기:
챗봇 그 이상을 위하여

© 2018 IBM Corporation 2Page
§ Speech to Text
§ Text to Speech
§ Watson Assistant
§ SIP Service
§ Watson Voice Agent
§ Lesson Learned
INDEX

ü 본 세션은 아직 공식적으로 지원하지 않는 ‘한국리전’
Voice Agent 기능에 대해 ＇개인’으로서 실험적으로
구축한 인공지능 콜센터에 대해 다루고 있습니다.
Disclaimer
ü 추후 Watson Voice Agent나 SIP 서비스의 업데이트에
따라 실습 방법이 달라질 수 있습니다.
ü 구체적인 현장 적용시에 데이터와 비즈니스 로직의
복잡성, IVR 환경에 따라 구현이 달라질 수 있습니다.

왓슨의 한국어 음성 인식 API
- AM + LM Customization
- Lightly supervised learning
Watson Speech to Text

Speech To Text
Narrowband (8kHz)는 전화상에서의 대화를 뜻하며, 콜센터 프로젝트 등이 사용되는 주파수이다. Broadband
(16kHz)는발화나일반적인대화를뜻하며인공지능스피커등에사용되고있다.
https://speech-to-text-demo.ng.bluemix.net/

일반적인 Speech To Text 트레이닝 데이터 생성 과정
이미있는음성파일을받아적거나,이미있는대화록을녹음하거나
Data Generation
(Text + Audio)
ü 텍스트데이터를통해LM(LanguageModel)이오디오데이터를통해AM(AcousticModel)을
생성하여활용

LightlySupervisedLearning을통해사람이직접음성파일의타임프레임을지정해주지않더라도미리입력된
텍스트를통해음성파일을학습함
ü 학습데이터를생성하는데걸리는시간을단축시킴

Speech To Text : cURL
Create a custom model
curl –X POST https://stream.watsonplatform.net/speech-to-text/api/v1/acoustic_customizations
Returns a model id called ‘customization_id’
Add a ZIP file containing audio (e.g. WAV files)
curl -X POST –data-binary @audiofiles.zip -H "Content-type: application/zip"
https://stream.watsonplatform.net/speech-to-
text/api/v1/acoustic_customizations/{customization_id}/audio/audio-name
Start training
curl –X POST https://stream.watsonplatform.net/speech-to-
text/api/v1/acoustic_customizations/{customization_id}/train
curl –X GET https://stream.watsonplatform.net/speech-to-
text/api/v1/acoustic_customizations/{customization_id}
Query the customization service to find status of training – it should return ‘available’
once training has completed successfully
Using the custom model with the STT service for recognition
curl https://stream.watsonplatform.net/speech-to-
text/api/v1/recognize?acoustic_customization_id={customization_id}

Public API for STT customization
API
Number
Method API URL Description
API-01 POST speech-to-text/api/v1/customizations
Create new custom model, returns a
'customization_id' GUID
API-02 GET speech-to-text/api/v1/customizations?language=en-US List custom models for a language
API-03 DELETE /api/v1/customizations/{customization_id} Delete custom model
API-04 GET /api/v1/customizations/{customization_id} Query contents of custom model
API-05 POST
/api/v1/customizations/{customization_id}/corpora/{corpus_na
me}
Adds training corpus data to custom model,
names it 'corpus_name'
API-06 GET /api/v1/customizations/{customization_id}/corpora Returns list of corpora in custom model
API-07 DELETE
/api/v1/customizations/{customization_id}/corpora/{corpus_na
me}
Deletes corpus resource named 'corpus_name'
API-08 POST /api/v1/customizations/{customization_id}/train
Starts training session (creates custom model for
use in STT service)
API-09 POST /api/v1/customizations/{customization_id}/words
Adds one or more custom words or
words+pronunciations to model
API-10 GET /api/v1/customizations/{customization_id}/words
Returns all custom words added to model as well
as out-of-vocab words found in the input corpus
API-11 PUT
/api/v1/customizations/{customization_id}/words/{word_name
}
Adds a single word 'word_name' to model
API-12 GET
}
Gets info about a single word 'word_name'
API-13 DELETE
}
Deletes a single word 'word_name'
API-14 POST /api/v1/customizations/{customization_id}/upgrade_model
Updates custom model to work with latest
release of the STT service
API-15 POST /api/v1/customizations/{customization_id}/reset Clears all corpora and words from model

왓슨의 한국어 음성 합성 API
- SSML
Watson Text to Speech

Text to Speech (Demo)
https://text-to-speech-demo.ng.bluemix.net/
TTS한국어버전의경우,IBMKorea에직접문의하면사용할수있으며,Aibril을통해서도사용해볼수있음

Text to Speech : cURL
Default/v1/synthesize (EN)
$ curl -X POST -u {username}:{password}
--header "Content-Type: application/json"
--data "{"text":"hello world"}"
--output hello_world.ogg
"https://stream.aibril-watson.kr/text-to-speech/api/v1/synthesize"
/v1/synthesize (KR) voice= youngmi, yuna
curl -X POST -u "bda90c8d-906f-4ef2-a578-8f01cfad4ff7:L05VI0Z8P34X" --header "Content-Type:
application/json" --data "{"text":"아이비엠에서 신규 법인폰을 개통하기 위해서는 유심구매가
필요합니다."}" --output hello_world1.ogg "https://stream.aibril-watson.kr/text-to-
speech/api/v1/synthesize?voice=yuna"
/v1/synthesize (KR) custom model create
curl -X POST -u "bda90c8d-906f-4ef2-a578-8f01cfad4ff7:L05VI0Z8P34X" --header "Content-
Type:application/json" --data "{"name":"cURL Test", "language":"ko-KR",
"description":"Customization test via cURL"}" "https://stream.aibril-watson.kr/text-to-
speech/api/v1/customizations"
curl -X GET -u {username}:{password}
"https://stream.aibril-watson.kr/text-to-speech/api/v1/customizations/{customization_id}"
/v1/synthesize (KR) custom model call

Text to Speech : cURL
/v1/synthesize Using SSML
curl -X POST -u "{username}:{password}" --header "Content-Type: application/json" --data
"{"text":"IBM에서 신규 법인폰을 개통하기 위해서는 <sub alias='유심'>USIM</sub> 구매가
필요합니다."}" --output hello_world3.ogg "https://stream.aibril-watson.kr/text-to-
speech/api/v1/synthesize?voice=yuna"
/v1/synthesize (KR) add custom words
curl -X POST -u "{username}:{password}" --header "Content-Type:application/json" --data "{"words":
[{"word":"IBM", "translation":"아이비엠"}, {"word":"USIM", "translation":"유심"}]}"
"https://stream.aibril-watson.kr/text-to-speech/api/v1/customizations/{custom_id}/words"
/v1/synthesize (KR) custom words list
curl -X GET -u "{username}:{password}" "https://stream.aibril-watson.kr/text-to-
speech/api/v1/customizations/{custom_id}/words"
curl -X POST -u "{username}:{password}" --header "Content-Type: application/json" --data
"{"text":"IBM에서 신규 법인폰을 개통하기 위해서는 USIM 구매가 필요합니다."}" --output
hello_world_cus_ko_1.ogg "https://stream.aibril-watson.kr/text-to-
speech/api/v1/synthesize?customization_id={custom_id}"
/v1/synthesize (KR) custom model synthesize

Text to Speech
https://watson-api-explorer.ng.bluemix.net/apis/text-to-speech-v1
WatsonAPIExplorer

Speech Synthesis Markup Language (SSML)
https://console.bluemix.net/docs/services/text-to-speech/SSML.html#ssml
SSML을활용하면음의높낮이Pitch,특정발음을교정해주는subalias등을활용할수있습니다.

Waston Assistant
(Formerly Watson Conversation)
왓슨의 한국어 챗봇 서비스

ChatBot UI/UX [5]
이제아래와같은이미지/터치엘리먼트는사용할수없습니다.오로지텍스트로만!

Watson Assistant
https://console.bluemix.net/docs/services/text-to-speech/SSML.html#ssml
한땀한땀농업적근면성을발휘하여DialogFlow를구성합니다.

Watson Assistant
[NewCredential]을통해WatsonAssistant챗봇의Credential을추가
**********
**********

전화 받는 서비스
- 버튼 입력 IVR
SIP Service: Twillo

SIP(Session Initiation Protocol) Service : Twillo
없을경우,Twillo와같은무료Trial계정을통해테스트를진행해볼수있음

SIPTrunking을통해전화를받는서비스(Inbound)를구현할수있음.

VoiceAgentEndpoint를SIP서비스에설정,필요시 DREndpoint를추가할수있음.
ü [ElasticSIPTrunkingdashboard]-[CreateSIPTrunk]-[Origination]-[SIPURI]항목에서VoiceAgent의SIP
주소를등록

[Numbers]탭에서[GetStartedwithPhoneNumbers]로무료미국번호를얻거나[BuyaNumber]를통해한국
전화번호를구입할수있음
ü [ElasticSIPTrunking]-[Numbers]에서새로발급받은번호를할당Assign해주어야함.
ü ElasticSIP를통해Calllog와과금등을확인할수있음.

IVR(interactive voice response) 기능을 테스트하고 싶을 경우
기존구축된IVR에추가적인연동작업필요.Twillo에서는현재영문/유료기능으로테스트가능[6]

왓슨 음성 비서(Watson Voice Agent)와
‘한국어’ 콜센터 구현
Watson Voice Agent

Watson Voice Agent
https://www.youtube.com/watch?v=LcTAkRZzuwo

Watson Voice Agent
SIP Service
전화
음성 인식
챗봇
음성합성

Watson Voice Agent
SIPService에서발급받은전화번호를입력한뒤,WatsonAssistant,SpeechtoText의Credential을추가합니다.
**********
**********

Watson Voice Agent
TexttoSpeech의Credential과EventForwarding용CloudantDB를추가합니다.
**********
**********
**********

Call flow from a customer to a live agent
이미기업에서사용하고있는IVR이나기업레벨의SBC등과연동도가능
https://www.ibm.com/support/knowledgecenter/SS4U29/contactctr.html?view=embed

Event Forwarding (Last Updated: 2018-08-24)
총3가지이벤트Forwarding지원,CallDetailRecord(CDR),TranscriptionEvents,WatsonAssistantturnsEvents

이벤트Event를통해DB에WatsonVoiceAgent데이터를저장하고활용할수있음
– Call detail record (CDR) 이벤트
시작 및 종료 시간, 종료 이유 및 대화 트랜잭션에 대한 세부 정보와 같이 단일 호출Single
Call에 대한 요약 정보가 들어 있습니다.
– IBM Watson™ Assistant Turn 이벤트
Voice Gateway가 Watson Assistant에 대한 각 요청Each request 후에 수신 한 즉각적인
JSON 응답이 포함되는 이벤트 정보가 들어 있습니다.
– Transcription 이벤트
발화Utterance가 감지 될 때마다 발행되며 발화 텍스트Utterance text, 신뢰 점수
Confidence score 및 세션 정보를 포함합니다. 버전 1.0.0.2 이상에서 지원됩니다.
ü 이벤트를HTTPPOSTRequests로보내어SplunkHTTPEventCollector(HEC)혹은REST서버와통합할
수있습니다.NoSQLDB나IBMCloudantDB로이벤트를저장할수도있습니다.

Cloudant DB
[CloudantDB생성]-[Credential추가]-[LAUNCHCLOUDANTDASHBOARD]-[CreateDatabase3개생성]

Calldetailrecordeventformat(UnitofAnalysis:Call)
https://www.ibm.com/support/knowledgecenter/SS4U29/reportingcdr.html

WatsonAssistantturneventformat(UnitofAnalysis:Request)
https://www.ibm.com/support/knowledgecenter/SS4U29/reportingconvturn.html#cloudant-assistant

Transcriptioneventformat(UnitofAnalysis:Utterance)
https://www.ibm.com/support/knowledgecenter/SS4U29/rttconfig.html?view=embed

Deploying Voice Gateway on a Kubernetes cluster in IBM Cloud
Github https://github.com/WASdev/sample.voice.gateway
Guide https://www.ibm.com/support/knowledgecenter/en/SS4U29/deploybmix.html

Lesson Learned
실제 구현하면서 느낀 점들

이제 실제 사용을 해봅시다!
다른 팀원들한테도 수줍게 번호를
알려줍시다.
두근반 세근반

Demo
https://soundcloud.com/yh-studio/watson-
voice-agent-poc-demo-korean

잠 깐!
음성 데이터 학습을
어떻게 시킨다고 했었죠?

이미있는음성파일을받아적거나,이미있는대화록을녹음하거나
Data Generation
(Text + Audio)
ü 텍스트데이터를통해LM(LanguageModel)이오디오데이터를통해AM(AcousticModel)을
생성하여활용

사람들은 인공지능에게 존댓말을
하지 않습니다!
User Behavior

인공지능 상담원이 받는다고
하면 말이 짧아집니다!
User Behavior

학습 데이터와 실제 데이터가
다르면?
Data

과적합 Overfitting!
Data

훈련데이터와실제데이터의차이가클수록과적합이발생할가능성이높음.
모의고사열심히풀었지만수능에처음보는유형이나온다면?
Overfitting 과적합

Overfitting 과적합
존댓말을학습했는데,사용자는반말로문의를하면어떻게될까?
긴문장을학습했는데,짧은문장으로질문한다면?

인공지능이 아닌척 최대한
자연스럽게 해보면 될까?

캘리포니아의 AI 상담원 고지 의무 [4]
https://www.pe.com/2018/10/30/best-in-law-must-you-disclose-what-your-bot-is-up-to-california-weighs-in-on-ai/
인공지능이사람을상대할때고지의의무를명문화

사용자로부터 발화되는 소음
예) 음... 어... 에....
사용자로부터 들어야 하는 대답
예) 응. 어. 예
각종 배경 소음(기종도 천차만별)
+
+
Background Noise

사람들이 챗봇 상담원의 말이
너무 길어지면 오랫동안 듣지
않습니다.
==
(자의반 타의반) 사람들이 챗봇의
말을 짜르는 경우가 많습니다.
Background Noise

기존 챗봇과 다르게,
챗봇은 짧은 시간 동안 많은 양의
정보를 전달해야 하고,
사용자는 더 긴 시간 동안 자신의
의도를 설명해주어야 합니다.

챗봇의 말은 짧아지고,
사람의 대답은 길어져야 한다.
적절히, 유도하는 멘트 필요!

전화에 구체적이고 특정한 목표가
있을 때, 더 잘 알아들음.
목표가 광범위할 수록 어려움.

Project Examples
IBM’s Watson to Listen in on 911 Calls https://www.meritalk.com/articles/ibms-watson-to-listen-in-on-911-calls/
Essextec CI delivers Cognitive Solutions with IBM GBS https://essextec.com/about/news/essextec-ci-delivers-cognitive-solutions-with-ibm-gbs
Association of Public-Safety Communications Officials (APCO) International Taps IBM Watson Capabilities to Evaluate and Report on Emergency
Calls https://essextec.com/wp-content/uploads/2017/08/IBM-Watson-APCO-press-release.pdf
The Association of Public-Safety Communications Officials (APCO)
International
ü IBM’s Watson to Listen in on 911 Calls

Project Examples
Mizuho Bank, Watson Technology installed in Call Centers preparing for next
generation channels
WatsonTechnology installed in Call Centers preparing for next generation channels
https://www.mizuhobank.com/mizuho_fintech/news/watson/index.html

Project Examples
Invoca Call Center
Invoca(2016), Invoca
embeds IBM’s Watson so
call centers can better
understand their customers
https://www.invoca.com/pr
ess/invoca-integrates-ibm-
watson-real-time-voice-
analytics/
https://marketingland.com/i
nvoca-embeds-ibms-watson-
call-centers-can-better-
understand-customers-
200376
https://blog.invoca.com/ibm
-watson-speech-text-turns-
phone-calls-invaluable-
marketing-data/

한국에서의 다음 성공사례는
어떤 기업이 될까요?

감사합니다.
실제 프로젝트를 고려하시는 경우,
부담없이 문의주세요.
Yunhomaeng@kr.ibm.com

References
[1] Chingwa Univ http://www.cs.nthu.edu.tw/~shwu/courses/ml/labs/08_CV_Ensembling/08_CV_Ensembling.html
[2] Penn Univ https://quantdev.ssri.psu.edu/tutorials/cross-validation-tutorial
[3] Sigmoidal ML c https://sigmoidal.io/
[4] https://www.pe.com/2018/10/30/best-in-law-must-you-disclose-what-your-bot-is-up-to-california-weighs-in-on-
ai/
[5] https://chatbotsmagazine.com/cheat-sheet-all-facebook-chatbot-interactions-4b14e4e00178
[6] https://www.twilio.com/docs/voice/tutorials/how-to-gather-user-input-via-keypad-python
[7] WatsonTechnology installed in Call Centers preparing for next generation channels
https://www.mizuhobank.com/mizuho_fintech/news/watson/index.html
[8] Invoca(2016), Invoca embeds IBM’s Watson so call centers can better understand their customers
https://www.invoca.com/press/invoca-integrates-ibm-watson-real-time-voice-analytics/
https://marketingland.com/invoca-embeds-ibms-watson-call-centers-can-better-understand-customers-200376
https://blog.invoca.com/ibm-watson-speech-text-turns-phone-calls-invaluable-marketing-data/
[9] IBM’s Watson to Listen in on 911 Calls https://www.meritalk.com/articles/ibms-watson-to-listen-in-on-911-calls/
[10] Essextec CI delivers Cognitive Solutions with IBM GBS https://essextec.com/about/news/essextec-ci-delivers-
cognitive-solutions-with-ibm-gbs
[11] Association of Public-Safety Communications Officials (APCO) International Taps IBM Watson Capabilities to
Evaluate and Report on Emergency Calls https://essextec.com/wp-content/uploads/2017/08/IBM-Watson-APCO-
press-release.pdf
[12] https://console.bluemix.net/docs/services/text-to-speech/SSML.html#ssml

Watson Voice Agent를 활용한 ‘한국어’ 인공지능 콜센터 제작하기: 챗봇 그 이상을 위하여 (IBM Devday 발표자료)

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