YIN, a fundamental frequency estimator for speech and music
In The Last Decade
doi.org/10.1121/1.1458024 →Countries where authors are citing YIN, a fundamental frequency estimator for speech and music
This map shows the geographic impact of YIN, a fundamental frequency estimator for speech and music. 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 YIN, a fundamental frequency estimator for speech and music with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites YIN, a fundamental frequency estimator for speech and music more than expected).
Fields of papers citing YIN, a fundamental frequency estimator for speech and music
This network shows the impact of YIN, a fundamental frequency estimator for speech and music. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the YIN, a fundamental frequency estimator for speech and music.
About YIN, a fundamental frequency estimator for speech and music
This paper, published in 2002, received 1.2k indexed citations . Written by Alain de Cheveigné and Hideki Kawahara covering the research area of Signal Processing. It is primarily cited by scholars working on Signal Processing (1.0k citations), Computer Vision and Pattern Recognition (420 citations) and Artificial Intelligence (365 citations). Published in The Journal of the Acoustical Society of America.
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/10.1121/1.1458024.