TellMyCV

TellMyCV is an early experiment in voice-interactive AI-driven Q&A, developed using Google Cloud Functions in Python. By analyzing a user's résumé and supplemental information, it enables visitors to verbally query a web interface and receive a spoken answer. This proof-of-concept predated widespread voice-interactive AI services, showcasing the potential of combining voice recognition, NLP, and data retrieval in a single, seamless user experience.

Voice-to-Text Integration

Utilized OpenAI's Whisper API to convert incoming audio queries into text.

Contextual Answers

Leveraged the CV and user details to form precise, token-efficient responses via OpenAI's language API.

Text-to-Speech Output

Employed Google APIs (or similar) to synthesize and deliver vocalized responses back to the user.

Early Innovator

Developed before mainstream adoption of voice-based AI assistants, highlighting the forward-thinking approach.

Google Cloud Functions

Offered scalable, serverless computing for efficient request handling.

Python-Based Backend

Provided a flexible platform for integrating AI and data processing workflows.

Whisper API & OpenAI Integration

Enabled accurate speech recognition and intelligent, context-aware answer generation.

Flutter Frontend

Delivered a responsive, user-friendly web interface for initiating voice queries and receiving responses.

Innovative Proof-of-Concept

Demonstrated the feasibility of voice-interactive Q&A long before widespread voice-based AI tools became common.

Limited Adoption at the Time

Although it didn't gain broad traction initially, it underscored the potential and value of early experimentation.

Showcase of Technical Ingenuity

Positioned as a pioneering step toward the seamless, voice-driven AI interactions now becoming standard.

On request: documentation, code snippets, or archival demos illustrating the concept's execution and potential.