Nevaan Goburdhun

Key Skills

Software

Label Studio

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Top Label Types

Audio Recording

Freelancer Overview

With over 22 years of experience in advanced publishing technologies, I bring a strong background in managing complex workflows, meticulous attention to detail, and precise handling of digital assets—skills directly relevant to data labeling and AI training data roles. I have extensive experience operating and maintaining technical systems, ensuring high-quality output and accuracy, and facilitating seamless communication between teams. My proficiency with digital media workflows, file management via FTP, and robust reporting ensures that I can deliver reliable, well-organized, and accurately annotated data. I am a quick learner, thrive in collaborative environments, and am committed to supporting team objectives while maintaining the highest standards of quality and efficiency.

Labeling Experience

Freelancer

Label StudioAudioAudio Recording

Specific data labeling tasks performed using "Label Studio" as the primary interface. The following tasks were performed on the audio data: Verbatim Transcription: Listening to raw audio segments and typing out the exact speech, including "disfluencies" (um, uh, stuttering) and non-standard grammar, to capture the authentic nature of human speech. Audio Segmentation (Diarization): Using Label Studio’s waveform interface to identifying and marking start/end times for different speakers (e.g., "Interviewer" vs. "Subject"). Sociolinguistic Tagging: Labeling specific acoustic regions where "code-switching" occurred (changing languages/dialects mid-sentence). Tagging emotional tone (e.g., Nostalgic, Distressed, Neutral) for sentiment analysis studies. Annotating specific regional slang or idioms that required cultural knowledge to interpret correctly. Metadata Classification: Assigning demographic attributes to speakers based on auditory cues and context (e.g., estimated age g

Specific data labeling tasks performed using "Label Studio" as the primary interface. The following tasks were performed on the audio data: Verbatim Transcription: Listening to raw audio segments and typing out the exact speech, including "disfluencies" (um, uh, stuttering) and non-standard grammar, to capture the authentic nature of human speech. Audio Segmentation (Diarization): Using Label Studio’s waveform interface to identifying and marking start/end times for different speakers (e.g., "Interviewer" vs. "Subject"). Sociolinguistic Tagging: Labeling specific acoustic regions where "code-switching" occurred (changing languages/dialects mid-sentence). Tagging emotional tone (e.g., Nostalgic, Distressed, Neutral) for sentiment analysis studies. Annotating specific regional slang or idioms that required cultural knowledge to interpret correctly. Metadata Classification: Assigning demographic attributes to speakers based on auditory cues and context (e.g., estimated age g

2025 - 2025

Education

Work History