Natural language processing (NLP) requires vast amounts of data to train AI to interpret human language. But data quality is just as important as quantity.
NLP training data with human insights can improve the accuracy, robustness, and interpretability of your NLP models.
With Toloka, you can build a predictable pipeline of high-quality training data that impacts your NLP algorithms.
Toloka handles almost any input data for NLP data labeling: text, audio, image, or video. Our platform supports data annotation for named entity recognition, sentiment analysis, speech recognition, text and intent classification, text recognition, and more.