Recommended Audiobooks Research
Research & Open Data
Recommended Audiobooks develops structured methods for describing how audiobooks listen — including narration, pacing, attention demands, complexity, mood, and listener fit. This page connects the public framework, archived methodology, source repository, and reusable dataset behind that work.
Audiobook Listener-Fit Framework
A structured way to describe the listening experience
Traditional ratings mostly answer whether people liked a title. The Audiobook Listener-Fit Framework is designed to describe how an audiobook listens and what kinds of listening situations or preferences may fit it well.
Core question: “Is this likely to be a good audiobook for me?”
Public research footprint
Open resources
Hugging Face Dataset
Browse the public listener-fit taxonomy in a reusable structured dataset with documented dimensions, definitions, scales, and evidence basis.
Open dataset →Zenodo DOI Archive
Access the persistent archived release of the Audiobook Listener-Fit Framework and use its DOI when citing the methodology.
Open DOI record →GitHub Repository
Review the public source repository and version history associated with the framework and its open materials.
Open GitHub →What is public
Dataset scope
The public dataset contains the framework and taxonomy used to organize listener-fit concepts. It does not expose the complete proprietary Recommended Audiobooks production database.
- Criterion identifiers and framework groups
- Criterion names and definitions
- Scales and interpretation guidance
- Evidence basis and confidence concepts
- Published quality dimensions and weights where applicable
Methodology
Evidence-informed, recording-aware profiles
The broader Recommended Audiobooks workflow can combine multiple public data and evidence sources, reconcile audiobook identity and narrator information, and organize relevant evidence into structured audiobook profiles. The framework separates quality-oriented dimensions from descriptive listening-profile traits so that “more” is not automatically treated as “better.”
Listener fit is descriptive rather than deterministic. It can help characterize an audiobook and support discovery, but it cannot guarantee that an individual listener will enjoy a title.
Citation
How to cite the framework
Cravedi, Kevin. Audiobook Listener-Fit Framework. Recommended Audiobooks.
https://doi.org/10.5281/zenodo.22815434
The public dataset is released under Creative Commons Attribution 4.0 International (CC BY 4.0).