Audio and Speech Data Annotation Projects
I worked on a large-scale Voice Assistant Dataset Annotation project, preparing approximately 500 hours of multi-speaker audio recordings from over 1,000 contributors across different regions and accents to train a virtual assistant AI. My tasks included transcribing spoken commands into accurate text, labeling speaker intent and command types, annotating emotional tone and background noise, and time-stamping audio segments for precise alignment. To ensure high-quality outputs, I followed strict annotation guidelines, conducted random spot checks, performed peer reviews, and tagged noisy or unusable segments. This work produced a structured, reliable dataset that significantly enhanced the AI’s speech recognition, intent detection, and natural language understanding capabilities.