CUED Publications database

Break it Down for Me: A Study in Automated Lyric Annotation

Sterckx, L and Naradowsky, J and Byrne, WJ and Demeester, T and Develder, C (2017) Break it Down for Me: A Study in Automated Lyric Annotation. In: EMNLP 2017: Conference on Empirical Methods in Natural Language Processing, -- to --, Copenhagen, Denmark.

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Comprehending lyrics, as found in songs and poems, can pose a challenge to human and machine readers alike. This motivates the need for systems that can under- stand the ambiguity and jargon found in such creative texts, and provide commentary to aid readers in reaching the correct interpretation. We introduce the task of automated lyric annotation (ALA). Like text simplification, a goal of ALA is to rephrase the original text in a more easily understand- able manner. However, in ALA the system must often include additional infor- mation to clarify niche terminology and abstract concepts. To stimulate research on this task, we release a large collection of crowdsourced annotations for song lyrics. We analyze the performance of translation and retrieval models on this task, measuring performance with both automated and human evaluation. We find that each model captures a unique type of information important to the task.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 25 Jul 2017 03:54
Last Modified: 18 Feb 2021 16:26