How to get the most out of machine learning systems

The father of modern speech recognition, Frederick Jelinek, once famously said: ‘Anytime a linguist leaves the group, the recognition rate goes up.’ Based on this logic, if the domain experts – the phonologists, in his case – were to be exchanged with pure engineers, the performance of the system would improve. Would this theory apply to a system that heavily utilises machine learning? Do the domain experts increase the performance, or is it the lack of them that is best for the system? When working in a highly specialised domain, such as the legal arena, which has clear, well-defined tasks, technology is provided to support, augment and increase productivity. It is often the case that both supervised machine learning techniques (i.e. there is access to labelled data) and unsupervised machine…

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