Audio-Based Understanding of Audiobook Narration Appeal
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Computer Science > Computation and Language
Title:Audio-Based Understanding of Audiobook Narration Appeal
Abstract:Narration is central to the audiobook listening experience, shaping how listeners engage with and understand the content. This work explores how narration qualities shape an audiobook's appeal, noting that their effects can vary by genre, title, and audience. We extract vocal and acoustic features (e.g., tone, pace, loudness) from LibriVox using pre-trained audio models and analyse their relationship with consumption data (specifically, view-rate) and their interplay with genre and title. Despite limited consumption data, we find that acoustic information alone has a robust association with appeal, even after accounting for title effects. We further validate these findings using more nuanced proprietary engagement metrics. To our knowledge, this is the first systematic computational study linking narration qualities, genre, title, and audiobook consumption, highlighting the potential of data-driven insights to improve audiobook personalisation and narrator casting.
| Comments: | Accepted to Interspeech 2026 |
| Subjects: | Computation and Language (cs.CL); Sound (cs.SD); Audio and Speech Processing (eess.AS) |
| Cite as: | arXiv:2607.02473 [cs.CL] |
| (or arXiv:2607.02473v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2607.02473
arXiv-issued DOI via DataCite (pending registration)
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