Web: http://arxiv.org/abs/2209.06913

Sept. 16, 2022, 1:16 a.m. | Jun Wang

cs.CL updates on arXiv.org arxiv.org

In this paper, we propose a novel architecture for direct extractive
speech-to-speech summarization, ESSumm, which is an unsupervised model without
dependence on intermediate transcribed text. Different from previous methods
with text presentation, we are aimed at generating a summary directly from
speech without transcription. First, a set of smaller speech segments are
extracted based on speech signal's acoustic features. For each candidate speech
segment, a distance-based summarization confidence score is designed for latent
speech representation measure. Specifically, we leverage the …

arxiv speech summarization

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