TalkLess blends extractive and abstractive speech summarization through LLM candidate generation and a weighted scoring function, then converts transcript edits to audio with VoiceCraft, evaluating favorably against an extractive baseline.
Extractive and Abstractive Explanations for Fact-Checking and Evaluation of News
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abstract
In this paper, we explore the construction of natural language explanations for news claims, with the goal of assisting fact-checking and news evaluation applications. We experiment with two methods: (1) an extractive method based on Biased TextRank -- a resource-effective unsupervised graph-based algorithm for content extraction; and (2) an abstractive method based on the GPT-2 language model. We perform comparative evaluations on two misinformation datasets in the political and health news domains, and find that the extractive method shows the most promise.
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TalkLess: Blending Extractive and Abstractive Speech Summarization for Editing Speech to Preserve Content and Style
TalkLess blends extractive and abstractive speech summarization through LLM candidate generation and a weighted scoring function, then converts transcript edits to audio with VoiceCraft, evaluating favorably against an extractive baseline.