Audio Annotator: Kannada-India

We are seeking contributors for a project focused on enhancing the quality and precision of audio-based AI models. The work involves tagging or labeling specific elements within audio files, such as identifying speakers, marking background noises, labeling emotions or speech patterns, and categorizing audio segments.

This project plays a vital role in improving the accuracy and contextual understanding of AI systems that process sound.

– Listen to audio recordings and accurately tag relevant elements (e.g., speakers, noises, emotions)

– Categorize audio segments such as speech, music, silence, or overlapping voices

– Mark timestamps for key events or changes in the recording

– Follow detailed annotation guidelines to ensure consistency and accuracy

– Native fluency in Kannada

– Minimum of 10 hours of availability per week

– Proficient listening skills with strong attention to detail

– Ability to follow complex instructions in English

– Prior experience in audio annotation or related work is preferred

– Familiarity with various accents, speech patterns, and audio quality levels is an advantage

– Pay rate is $2.00 per audio hour.

– On average, contributors can complete 1 audio hour per working hour, which equals $2.00 per audio hour.

– Payments are based on the total audio processed (per audio hour), not the number of hours worked. Actual earnings depend on speed and accuracy.

Join us in ensuring high-quality, engaging audio data for global AI systems.

Apply now to be part of Project Oak!