A computational study on outliers in world music
সংরক্ষণ করুন:
| প্রকাশিত: | PLoS One vol. 12, no. 12 (Dec 2017), p. e0189399 |
|---|---|
| প্রধান লেখক: | |
| অন্যান্য লেখক: | , |
| প্রকাশিত: |
Public Library of Science
|
| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | Citation/Abstract Full Text Full Text - PDF |
| ট্যাগগুলো: |
কোনো ট্যাগ নেই, প্রথমজন হিসাবে ট্যাগ করুন!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 1978297573 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1932-6203 | ||
| 024 | 7 | |a 10.1371/journal.pone.0189399 |2 doi | |
| 035 | |a 1978297573 | ||
| 045 | 2 | |b d20171201 |b d20171231 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Panteli, Maria | |
| 245 | 1 | |a A computational study on outliers in world music | |
| 260 | |b Public Library of Science |c Dec 2017 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers’. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness’ of the music of each country. | |
| 653 | |a Social | ||
| 653 | |a International conferences | ||
| 653 | |a Outliers (statistics) | ||
| 653 | |a Similarity | ||
| 653 | |a Spatial analysis | ||
| 653 | |a Computation | ||
| 653 | |a Music | ||
| 653 | |a Computer science | ||
| 653 | |a African music | ||
| 653 | |a Information retrieval | ||
| 653 | |a Signal processing | ||
| 653 | |a Digital music | ||
| 653 | |a Data analysis | ||
| 653 | |a Computer applications | ||
| 653 | |a Statistical analysis | ||
| 653 | |a World music | ||
| 653 | |a Sound | ||
| 653 | |a Data processing | ||
| 653 | |a Data mining | ||
| 653 | |a Ethnomusicology | ||
| 653 | |a Hypotheses | ||
| 653 | |a Multimedia | ||
| 653 | |a Studies | ||
| 653 | |a Methods | ||
| 653 | |a Audio data | ||
| 653 | |a Semantics | ||
| 653 | |a Uniqueness | ||
| 653 | |a Correlation analysis | ||
| 653 | |a Feasibility studies | ||
| 653 | |a Software | ||
| 653 | |a Comparative analysis | ||
| 653 | |a Correlation | ||
| 653 | |a Artificial intelligence | ||
| 700 | 1 | |a Benetos, Emmanouil | |
| 700 | 1 | |a Dixon, Simon | |
| 773 | 0 | |t PLoS One |g vol. 12, no. 12 (Dec 2017), p. e0189399 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1978297573/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/1978297573/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1978297573/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |