A model for the prediction of thresholds, loudness, and partial loudness

511 indexed citations

Abstract

loading...

About

This paper, published in 1997, received 511 indexed citations. Written by Brian C. J. Moore, Brian R. Glasberg and Thomas Baer covering the research area of Cognitive Neuroscience, Speech and Hearing and Automotive Engineering. It is primarily cited by scholars working on Cognitive Neuroscience (350 citations), Signal Processing (252 citations) and Speech and Hearing (205 citations). Published in Journal of the Audio Engineering Society.

In The Last Decade

doi.org/w6419676 →

Countries where authors are citing A model for the prediction of thresholds, loudness, and partial loudness

Specialization
Citations

This map shows the geographic impact of A model for the prediction of thresholds, loudness, and partial loudness. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by A model for the prediction of thresholds, loudness, and partial loudness with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A model for the prediction of thresholds, loudness, and partial loudness more than expected).

Fields of papers citing A model for the prediction of thresholds, loudness, and partial loudness

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of A model for the prediction of thresholds, loudness, and partial loudness. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A model for the prediction of thresholds, loudness, and partial loudness.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/w6419676.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026