<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vassilakis, D</style></author><author><style face="normal" font="default" size="100%">Anagnostopoulou, Ch.</style></author><author><style face="normal" font="default" size="100%">Georgaki, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Jazz Mapping: an analytical and computational approach to Jazz improvisation</style></title><secondary-title><style face="normal" font="default" size="100%">SMC</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><publisher><style face="normal" font="default" size="100%">Malaga University</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">“Jazz mapping&quot; is a multi-layered analytical approach to jazz improvisation. It is based on hierarchical segmentation and categorization of segments, or constituents, according to their function in the overall improvisation. The approach aims at identifying higher-level semantics of&lt;br&gt;transcribed and recorded jazz solos. At these initial stages, analytical decisions are rather exploratory and rely on the input of one of the authors and experienced jazz performer. &lt;br&gt;We apply the method to two well-known solos, by Sonny Rollins and Charlie Parker, and discuss how improvisations resemble story-telling, employing a broad range of structural, expressive and technical tools, usually associated with linguistic production, experience, and meaning. We elucidate the implicit choices of experienced jazz improvisers, who have developed a strong command over the language and can communicate expressive intent, elicit emotional responses, and unfold&lt;br&gt;musical “stories” that are memorable and enjoyable to&lt;br&gt;fellow musicians and listeners. We also comment on potential&lt;br&gt;artificial intelligence applications of this work to music research and performance.</style></abstract></record></records></xml>