CORDIS Project
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This project aims to improve machine learning methods for natural language processing by utilizing diverse data sources with varying levels of supervision. It focuses on developing algorithms and systems for tasks like document classification and speech recognition.
A major challenge in machine learning and artificial intelligence is to reduce the dependency in full direct supervision and learn from various undirected resources as well.
Most successful machine-learning systems require some amount of human supervision.
Currently, a dominant paradigm for building a statistical parser, for example, is to first have human annotators to manually parse a large amount of sentences, and then use the parsed sentences to learn the parameters of the parsing system.
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