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Author, Editor

Author(s):

Stupar, Aleksandar
Michel, Sebastian

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Editor(s):

Berendt, Bettina
de Vries, Arjen
Fan, Weinfei
Macdonald, Craig

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dblp
dblp
dblp

Not MPII Editor(s):

Berendt, Bettina
de Vries, Arjen
Fan, Weinfei
Macdonald, Craig

BibTeX cite key*:

StuparM2011b

Title, Booktitle

Title*:

PICASSO - Automated Soundtrack Suggestion for Multi-Modal Data

Booktitle*:

CIKM'11 : Proceedings of the 2011 ACM International Conference on Information and Knowledge Management

Event, URLs

URL of the conference:

http://www.cikm2011.org/

URL for downloading the paper:

http://doi.acm.org/10.1145/2063576.2064027

Event Address*:

Glasgow, UK

Language:

English

Event Date*
(no longer used):


Organization:

Association for Computing Machinery (ACM)

Event Start Date:

24 October 2011

Event End Date:

28 October 2011

Publisher

Name*:

ACM

URL:


Address*:

New York, NY

Type:


Vol, No, Year, pp.

Series:


Volume:


Number:


Month:


Pages:

2589-2592

Year*:

2011

VG Wort Pages:


ISBN/ISSN:

978-1-4503-0717-8

Sequence Number:


DOI:

10.1145/2063576.2064027



Note, Abstract, ©


(LaTeX) Abstract:

We demonstrate PICASSO, a novel approach to soundtrack recommendation. Given text, video, or image documents, PICASSO selects the best fitting music pieces, out of a given set of files, for instance, a user's personal mp3 collection. This task, commonly referred to as soundtrack suggestion, is non-trivial as it requires a lot of human attention and a good deal of experience, with master pieces distinguished, e.g., with the Academy Award for Best Original Score. We put forward PICASSO to solve this task in a fully automated way. We address the problem by extracting the required information, in form of music/screenshot samples, from available contemporary movies, making the training set easily obtainable. The training set is further extended with information acquired from movie scripts and subtitles, giving us a richer description of the action and atmosphere expressed in a particular movie scene. Although the number of applications for this approach is very large, we focus on two selected applications. First, we consider recommendation of the soundtrack for the slide show generation based on the given set of images. Second, we consider recommending a soundtrack as the background music for given audio books.



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Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Databases and Information Systems Group

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{StuparM2011b,
AUTHOR = {Stupar, Aleksandar and Michel, Sebastian},
EDITOR = {Berendt, Bettina and de Vries, Arjen and Fan, Weinfei and Macdonald, Craig},
TITLE = {PICASSO - Automated Soundtrack Suggestion for Multi-Modal Data},
BOOKTITLE = {CIKM'11 : Proceedings of the 2011 ACM International Conference on Information and Knowledge Management},
PUBLISHER = {ACM},
YEAR = {2011},
ORGANIZATION = {Association for Computing Machinery (ACM)},
PAGES = {2589--2592},
ADDRESS = {Glasgow, UK},
ISBN = {978-1-4503-0717-8},
DOI = {10.1145/2063576.2064027},
}


Entry last modified by Anja Becker, 02/21/2013
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Editor(s)
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Created
08/09/2011 11:38:05 AM
Revision
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Editor
Anja Becker
Sebastian Michel


Edit Date
15.03.2012 14:08:36
08/09/2011 11:38:05 AM


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