Jigglypuff Audio Transcription (Appen)
Currently project size is around 4 batches of 30 people each. They gonna onboard many later as per the client needs. Right now I'm delivering quality data labelling for the Jigglypuff on appen/crowdgen.
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Working with platforms like Outlier, CrowdGen, and Atlas, I have practical experience with a variety of AI training data and labelling projects. I contributed to high-quality data annotation on the Aether project (Outlier), emphasising precision, consistency, and respect to guidelines. Additionally, I worked on the Jigglypuff audio transcription project, where I honed my attention to detail, listening skills, and capacity to effectively record spoken content in a variety of audio environments. I also have experience with CrowdGen and Atlas image and video annotation tasks, such as action detection, segmentation, and object interaction labelling. My ability to adhere to intricate annotation rules, maintain quality under pressure, and reduce mistakes like hallucinations or missed actions has improved as a result of these initiatives. I am a dependable contributor to AI training workflows because of my versatility across many data formats (audio, picture, and video) and dedication to accuracy.
Currently project size is around 4 batches of 30 people each. They gonna onboard many later as per the client needs. Right now I'm delivering quality data labelling for the Jigglypuff on appen/crowdgen.
We were allowed to work not more than 4 weeks, So I followed the project guidelines carefully. Team once appreciated me for quality work.
Bachelor of Engineering, Computer Science and Engineering
ReactJS Developer