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Hindi Fluency Roleplay Chatbot
예산
$15~$25 USD
예상 기간
4~6개월
난이도
전문가
기술 스택
Python
Node.js
Natural Language Processing
AI Chatbot
Conversational AI
Mobile App Development
Web Development
Speech-to-Text
Text-to-Speech
Database
Cloud API Integration
Spaced Repetition System (SRS)
AI 분석 요약
친근한 언어 파트너 역할을 하는 힌디어 회화 연습 챗봇을 개발하는 프로젝트입니다. 일상 시나리오 기반의 대화와 대화 기록을 활용한 동적 반복 학습 퀴즈 기능이 핵심이며, Hinglish 인식 및 정제된 힌디어 유도, 웹/모바일 음성/텍스트 입출력 구현 역량이 요구됩니다.
프로젝트 원문 설명
I want to launch a conversational practice bot that feels like a friendly language partner rather than a rigid tutor. The core flow starts with the bot itself proposing everyday scenarios—ordering a cup of chai at a Connaught Place café, asking an auto-rickshaw driver for directions, checking in at a hotel in Jaipur—and guiding the learner through the dialogue. As we talk, the system must recognise and respond to natural Hinglish, yet steer the learner gently toward polished, formal Hindi without sounding patronising.
Right after each session, the same chat history should feed a dynamic quiz: the bot plucks out the trickier words or phrases (for example anubhav, prakriti), schedules them with spaced-repetition logic, and surfaces them in later chats until the learner shows mastery. No static vocabulary lists—everything adapts to the user’s real mistakes and hesitations.
Target environments are both a mobile app and a web interface. Learners will be free to type or speak, so the build needs seamless text I/O plus speech-to-text and text-to-speech hooks. I am open to whichever stack you are comfortable with—Rasa, Dialogflow CX, or a custom NLP pipeline in Python or Node.js—so long as:
• the scenario engine can expand easily with new role-plays,
• Hinglish code-switch detection is accurate enough to nudge, not scold,
• quizzes follow a true SRS algorithm (SM-2 or similar), and
• voice and text remain in sync across web and mobile.
Please include a brief outline of your proposed architecture, any pretrained language models or Hindi ASR/TTS services you would leverage, and a timeline for an MVP that covers at least three role-play scenes and the adaptive quiz loop.
Right after each session, the same chat history should feed a dynamic quiz: the bot plucks out the trickier words or phrases (for example anubhav, prakriti), schedules them with spaced-repetition logic, and surfaces them in later chats until the learner shows mastery. No static vocabulary lists—everything adapts to the user’s real mistakes and hesitations.
Target environments are both a mobile app and a web interface. Learners will be free to type or speak, so the build needs seamless text I/O plus speech-to-text and text-to-speech hooks. I am open to whichever stack you are comfortable with—Rasa, Dialogflow CX, or a custom NLP pipeline in Python or Node.js—so long as:
• the scenario engine can expand easily with new role-plays,
• Hinglish code-switch detection is accurate enough to nudge, not scold,
• quizzes follow a true SRS algorithm (SM-2 or similar), and
• voice and text remain in sync across web and mobile.
Please include a brief outline of your proposed architecture, any pretrained language models or Hindi ASR/TTS services you would leverage, and a timeline for an MVP that covers at least three role-play scenes and the adaptive quiz loop.
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