Quantifying the morphosyntactic content of Brown Clusters

When:
Thursday, May 30, 2019, 11:00 am - 12:00 pm PSTiCal
Where:
Conf. Rm #689
This event is open to the public.
Type:
Nl Seminar
Speaker:
Manuel Ciosici (Aarhus University)
Video Recording:
https://bluejeans.com/s/diiPj/
Description:

Abstract: Brown and Exchange word clusters have long been successfully used as word representations in Natural Language Processing (NLP) systems. Their success has been attributed to their seeming ability to represent both semantic and syntactic information. Using corpora representing several language families, we test the hypothesis that Brown and Exchange word clusters are highly effective at encoding morphosyntactic information. Our experiments show that word clusters are highly capable of distinguishing Parts of Speech. We show that increases in Average Mutual Information, the clustering algorithms' optimization goal, are highly correlated with improvements in encoding of morphosyntactic information. Our results provide empirical evidence that downstream NLP systems addressing tasks dependent on morphosyntactic information can benefit from word cluster features.

Bio:

Manuel is a soon-to-graduate Ph.D. student at Aarhus University, Denmark. His research is focused on understanding the kinds of information encoded in word representations and how that information can be used in downstream NLP applications.

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