  This paper provides a computational analysis of poetry reading audio signals
at a large scale to unveil the musicality within professionally-read poems.
Although the acoustic characteristics of other types of spoken language have
been extensively studied, most of the literature is limited to narrative speech
or singing voice, discussing how different they are from each other. In this
work, we develop signal processing methods, which are tailored to capture the
unique acoustic characteristics of poetry reading based on their silence
patterns, temporal variations of local pitch, and beat stability. Our
large-scale statistical analyses on three big corpora, each of which consists
of narration (LibriSpeech), singing voice (Intonation), and poetry reading
(from The Poetry Foundation), discover that poetry reading does share some
musical characteristics with singing voice, although it may also resemble
narrative speech.
