Who’s playing? Towards machine-assisted identification of jazz trumpeters by timbre

Lazar, Janet G.; Lesk, Michael

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https://hdl.handle.net/2142/89373 Copy

Description

Title

Who’s playing? Towards machine-assisted identification of jazz trumpeters by timbre

Author(s)

Lazar, Janet G.; Lesk, Michael

Issue Date

2016-03-15

Keyword(s)

• jazz information retrieval
• music information retrieval
• performer identification
• timbre recognition
• individuality in music performance

Abstract

The goal of our proposed study is to contribute to the growing research in machine-assisted identification of jazz performers. In particular, we seek to identify unknown jazz trumpeters. We plan to take an approach that has not received recent attention; namely, using human observation to compare spectrograms and other data representing musical timbre. We believe that human observation, when combined with machine learning, will improve accuracy of timbre recognition and performer identification. We will collect 100 music samples: five each from 20 trumpeters. We will manually sort spectrograms and other data in order to distinguish the most salient timbre characteristics. Once we choose those features, we will use a computer to filter for them. If our approach is successful, we will develop a larger database of trumpet solos.

Publisher

iSchools

Series/Report Name or Number

IConference 2016 Proceedings

Type of Resource

text

Language

eng

Permalink

http://hdl.handle.net/2142/89373

DOI

https://doi.org/10.9776/16481

Copyright and License Information

Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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