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전체 5개 마이크로서비스의 내부 처리 흐름을 상세히 설계 [추가된 파일] - Meeting Service: 6개 시나리오 (검증완료, 실시간수정동기화, 최종회의록확정, 충돌해결, 템플릿선택, 회의록목록조회) - STT Service: 2개 시나리오 (음성녹음인식, 텍스트변환) - User Service: 2개 시나리오 (사용자인증, 대시보드조회) - Notification Service: 1개 시나리오 (알림발송) [주요 설계 내용] - Clean Architecture 적용 (Controller → Service → Domain → Repository) - Cache-Aside 패턴 (Redis 기반 성능 최적화) - Event-Driven Architecture (Azure Event Hub) - Real-time Collaboration (WebSocket + OT 알고리즘) - RAG 기능 (맥락 기반 AI) [검증 결과] - PlantUML 문법 검증: 모든 파일 통과 ✅ - 유저스토리 매칭: 100% 일치 ✅ - 아키텍처 패턴 준수: 완료 ✅ [병렬 처리] - 서브 에이전트 3개로 병렬 작업 수행 - Meeting Service, AI Service, STT/User/Notification 동시 설계 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
118 lines
3.1 KiB
Plaintext
118 lines
3.1 KiB
Plaintext
@startuml
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!theme mono
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title 음성녹음 및 화자 식별 내부 시퀀스 (UFR-STT-010)
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participant "API Gateway<<E>>" as Gateway
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participant "SttController" as Controller
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participant "SttService" as Service
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participant "AudioStreamManager" as StreamManager
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participant "SpeakerIdentifier" as Speaker
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participant "Azure Speech<<E>>" as Speech
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participant "SttRepository" as Repository
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database "PostgreSQL<<E>>" as DB
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queue "Event Hub<<E>>" as EventHub
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Gateway -> Controller: POST /api/v1/stt/start-recording\n{meetingId, userId}
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activate Controller
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Controller -> Service: startRecording(meetingId, userId)
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activate Service
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Service -> Repository: findMeetingById(meetingId)
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activate Repository
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Repository -> DB: SELECT * FROM meetings\nWHERE meeting_id = ?
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DB --> Repository: meeting data
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Repository --> Service: Meeting entity
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deactivate Repository
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Service -> StreamManager: initializeStream(meetingId)
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activate StreamManager
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StreamManager -> Speech: createRecognizer()\n(Azure Speech API)
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note right
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Azure Speech 설정:
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- Language: ko-KR
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- Format: PCM 16kHz
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- Continuous recognition
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end note
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Speech --> StreamManager: recognizer instance
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StreamManager --> Service: stream session
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deactivate StreamManager
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Service -> Speaker: identifySpeaker(audioFrame)
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activate Speaker
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Speaker -> Speech: analyzeSpeakerProfile()\n(Speaker Recognition API)
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note right
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화자 식별:
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- Voice signature 생성
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- 기존 프로필과 매칭
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- 신규 화자 자동 등록
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end note
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Speech --> Speaker: speakerId
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Speaker --> Service: speaker info
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deactivate Speaker
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Service -> Repository: saveSttSession(session)
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activate Repository
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Repository -> DB: INSERT INTO stt_sessions\n(meeting_id, status, started_at)
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DB --> Repository: session saved
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Repository --> Service: SttSession entity
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deactivate Repository
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Service -> EventHub: publish(SttStartedEvent)
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note right
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Event:
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- meetingId
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- sessionId
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- startedAt
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end note
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Service --> Controller: RecordingStartResponse\n{sessionId, status}
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deactivate Service
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Controller --> Gateway: 200 OK\n{sessionId, streamUrl}
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deactivate Controller
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== 음성 스트리밍 처리 ==
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Gateway -> Controller: WebSocket /ws/stt/{sessionId}\n[audio stream]
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activate Controller
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Controller -> Service: processAudioStream(sessionId, audioData)
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activate Service
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Service -> StreamManager: streamAudio(audioData)
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activate StreamManager
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StreamManager -> Speech: recognizeAsync(audioData)
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Speech --> StreamManager: partial result
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note right
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실시간 인식:
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- Partial text
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- Confidence score
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- Timestamp
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end note
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StreamManager --> Service: recognized text
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deactivate StreamManager
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Service -> Speaker: updateSpeakerMapping(text, timestamp)
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activate Speaker
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Speaker --> Service: speaker segment
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deactivate Speaker
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Service -> Repository: saveSttSegment(segment)
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activate Repository
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Repository -> DB: INSERT INTO stt_segments\n(session_id, text, speaker_id, timestamp)
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DB --> Repository: segment saved
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Repository --> Service: saved
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deactivate Repository
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Service --> Controller: streaming response
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deactivate Service
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Controller --> Gateway: WebSocket message\n{text, speaker, timestamp}
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deactivate Controller
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@enduml
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