KPDROP: Improving Absent Keyphrase Generation
Jishnu Ray Chowdhury, Seo Yeon Park, Tuhin Kundu, Cornelia Caragea · 2022
Keyphrase generation is the task of generating phrases (keyphrases) that summarize the main topics of a given document.Keyphrases can be either present or absent from the given document.While the extraction of present keyphrases has received much attention in the past, only recently a stronger focus has been placed on the generation of absent keyphrases.However, generating absent keyphrases is challenging; even the best methods show only a modest degree of success.In this paper, we propose a model-agnostic approach called keyphrase dropout (or KPDROP) to improve absent keyphrase generation.In this approach, we randomly drop present keyphrases from the document and turn them into artificial absent keyphrases during training.We test our approach extensively and show that it consistently improves the absent performance of strong baselines in both supervised and resourceconstrained semi-supervised settings 1 .Original Input Before Applying KPDROP: Input: The Hearing-Aid Speech Perception Index (HASPI) This paper presents a new index for predicting speech intelligibility for normal-hearing and hearing-impaired listeners.The Hearing-Aid Speech Perception Index (HASPI) is based on a model of the auditory periphery that incorporates changes due to hearing loss .The index compares the envelope and temporal fine structure outputs of the auditory model for a reference signal to the outputs of the model for the signal under test.The auditory model for the reference signal is set for normal hearing, while the model for the test signal incorporates the peripheral hearing loss .