Music Information Retrieval: An Inspirational Guide to Transfer from Related Disciplines

TitleMusic Information Retrieval: An Inspirational Guide to Transfer from Related Disciplines
Publication TypeBook Chapter
Year of Publication2012
AuthorsWeninger, F, Schuller, B, Liem, CCS, Kurth, F, Hanjalic, A
EditorMüller, M, Goto, M, Schedl, M
Book TitleMultimodal Music Processing
Series TitleDagstuhl Follow-Ups
Volume3
Pagination195–216
PublisherSchloss Dagstuhl–Leibniz-Zentrum für Informatik
CityDagstuhl, Germany
ISBN1868-8977
ISBN Number978-3-939897-37-8
Keywordscross-domain methodology transfer, evaluation, Feature Extraction, human factors, machine learning, multimodal fusion
Abstract

The emerging field of Music Information Retrieval (MIR) has been influenced by neighboring domains in signal processing and machine learning, including automatic speech recognition, image processing and text information retrieval. In this contribution, we start with concrete examples for methodology transfer between speech and music processing, oriented on the building blocks of pattern recognition: preprocessing, feature extraction, and classification/decoding. We then assume a higher level viewpoint when describing sources of mutual inspiration derived from text and image information retrieval. We conclude that dealing with the peculiarities of music in MIR research has contributed to advancing the state-of-the-art in other fields, and that many future challenges in MIR are strikingly similar to those that other research areas have been facing.

URLhttp://drops.dagstuhl.de/opus/volltexte/2012/3473
DOIhttp://dx.doi.org/10.4230/DFU.Vol3.11041.195