Automatic Generation of Factual News Headlines in Finnish
Maximilian Koppatz, Khalid Alnajjar, Mika H\"am\"al\"ainen, Thierry, Poibeau
TL;DR
This paper introduces a Finnish news headline generation system using a fine-tuned GPT-2 model, evaluated by journalists, to assist in news production.
Contribution
It develops the first Finnish GPT-2 model and applies it to generate news headlines, demonstrating its practical usability in media workflows.
Findings
The system effectively generates relevant headlines.
Expert evaluation confirms its usefulness.
The approach facilitates faster news production.
Abstract
We present a novel approach to generating news headlines in Finnish for a given news story. We model this as a summarization task where a model is given a news article, and its task is to produce a concise headline describing the main topic of the article. Because there are no openly available GPT-2 models for Finnish, we will first build such a model using several corpora. The model is then fine-tuned for the headline generation task using a massive news corpus. The system is evaluated by 3 expert journalists working in a Finnish media house. The results showcase the usability of the presented approach as a headline suggestion tool to facilitate the news production process.
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Video Analysis and Summarization
MethodsMulti-Head Attention · Attention Is All You Need · Cosine Annealing · Byte Pair Encoding · Weight Decay · Refunds@Expedia|||How do I get a full refund from Expedia? · Linear Layer · Dense Connections · Attention Dropout · Residual Connection