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Alberto Introini

dblp:180/5702 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Audio and music processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing › music analysis
expressive performance analysis
0.212016
Audio Features Affected by Music Expressiveness: Experimental Setup and Preliminary Results on Tuba Players · SIGIR 2016
Audio and music processing
music information retrieval
0.212016
Audio Features Affected by Music Expressiveness: Experimental Setup and Preliminary Results on Tuba Players · SIGIR 2016

Methods — techniques the papers use, named apart from their topics

statistical analysis · 0.2machine learning · 0.2
YearPublicationVenuePosition
2016 Audio Features Affected by Music Expressiveness: Experimental Setup and Preliminary Results on Tuba Players
abstract
Within a Music Information Retrieval perspective, the goal of the study presented here is to investigate the impact on sound features of the musician's affective intention, namely when trying to intentionally convey emotional contents via expressiveness. A preliminary experiment has been performed involving 10 tuba players. The recordings have been analysed by extracting a variety of features, which have been subsequently evaluated by combining both classic and machine learning statistical techniques. Results are reported and discussed.
Alberto Introini, Giorgio Presti, Giuseppe Boccignone
SIGIR1