Attention in NLP
Explore the core principles of attention mechanisms and their transformative impact on tasks like neural machine translation.
Let's further explore the concepts of attention mechanisms and transformers by using the example of neural machine translation (NMT). NMT is the computational approach that utilizes artificial neural networks to automatically and contextually translate text from one language to another. It’s a crucial task in natural language processing (NLP), relying on parallel datasets, denoted as X and Y, which contain sentences and their translations in different languages.
Challenge of unaligned data
One classic example of unaligned data, where there isn't a direct word-to-word correspondence between input and output sentences, is the Rosetta Stone. This alignment challenge is pivotal for machine translation but is rarely encountered.
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