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Found 2 papers, 1 papers with code
Scalable Data Annotation Pipeline for High-Quality Large Speech Datasets Development
Our A/B testing and pilot results demonstrated the HITL pipeline can improve annotation speed and capacity by at least 80% and quality is comparable to or higher than manual double pass annotation.
Semi-Supervised Learning with Auxiliary Evaluation Component for Large Scale e-Commerce Text Classification
To tackle this challenge, in this paper, we propose a semi-supervised learning method to utilize unlabeled data and user feedback signals to improve the performance of ML models.
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