neha shriwas

At CrowdGen, I reviewed and evaluated language and text data against project instructions, annotation guidelines, and quality criteria. I assessed translation outputs for meaning, accuracy, fluency, and readability.

I identified linguistic errors, unclear expressions, omissions, and inconsistencies, and revised translations when task guidelines required it. I also provided ratings, corrections, or written feedback when the project workflow called for them.

My academic projects include a smart glove that converts hand gestures into text, a Python virtual desktop assistant with speech recognition and text-to-speech, and a personal finance manager. I’m interested in contributing to LLM response evaluation, text annotation, fact-checking, summarization, and AI model quality improvement.