語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Music Similarity and Retrieval = An ...
~
Schedl, Markus.
Music Similarity and Retrieval = An Introduction to Audio- and Web-based Strategies /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Music Similarity and Retrieval/ by Peter Knees, Markus Schedl.
其他題名:
An Introduction to Audio- and Web-based Strategies /
作者:
Knees, Peter.
其他作者:
Schedl, Markus.
面頁冊數:
XX, 299 p. 82 illus., 47 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Information storage and retrieval. -
電子資源:
https://doi.org/10.1007/978-3-662-49722-7
ISBN:
9783662497227
Music Similarity and Retrieval = An Introduction to Audio- and Web-based Strategies /
Knees, Peter.
Music Similarity and Retrieval
An Introduction to Audio- and Web-based Strategies /[electronic resource] :by Peter Knees, Markus Schedl. - 1st ed. 2016. - XX, 299 p. 82 illus., 47 illus. in color.online resource. - The Information Retrieval Series,361871-7500 ;. - The Information Retrieval Series,35.
1 Introduction to Music Similarity and Retrieval -- 2 Basic Methods of Audio Signal Processing -- 3 Audio Feature Extraction for Similarity Measurement -- 4 Semantic Labeling of Music -- 5 Contextual Music Meta-data: Comparison and Sources -- 6 Contextual Music Similarity, Indexing, and Retrieval -- 7 Listener-centered Data Sources and Aspects: Traces of Music Interaction -- 8 Collaborative Music Similarity and Recommendation -- 9 Applications -- 10 Grand Challenges and Outlook -- Appendix.
This book provides a summary of the manifold audio- and web-based approaches to music information retrieval (MIR) research. In contrast to other books dealing solely with music signal processing, it addresses additional cultural and listener-centric aspects and thus provides a more holistic view. Consequently, the text includes methods operating on features extracted directly from the audio signal, as well as methods operating on features extracted from contextual information, either the cultural context of music as represented on the web or the user and usage context of music. Following the prevalent document-centered paradigm of information retrieval, the book addresses models of music similarity that extract computational features to describe an entity that represents music on any level (e.g., song, album, or artist), and methods to calculate the similarity between them. While this perspective and the representations discussed cannot describe all musical dimensions, they enable us to effectively find music of similar qualities by providing abstract summarizations of musical artifacts from different modalities. The text at hand provides a comprehensive and accessible introduction to the topics of music search, retrieval, and recommendation from an academic perspective. It will not only allow those new to the field to quickly access MIR from an information retrieval point of view but also raise awareness for the developments of the music domain within the greater IR community. In this regard, Part I deals with content-based MIR, in particular the extraction of features from the music signal and similarity calculation for content-based retrieval. Part II subsequently addresses MIR methods that make use of the digitally accessible cultural context of music. Part III addresses methods of collaborative filtering and user-aware and multi-modal retrieval, while Part IV explores current and future applications of music retrieval and recommendation.>.
ISBN: 9783662497227
Standard No.: 10.1007/978-3-662-49722-7doiSubjects--Topical Terms:
1069252
Information storage and retrieval.
LC Class. No.: QA75.5-76.95
Dewey Class. No.: 025.04
Music Similarity and Retrieval = An Introduction to Audio- and Web-based Strategies /
LDR
:03961nam a22004215i 4500
001
976556
003
DE-He213
005
20200710134900.0
007
cr nn 008mamaa
008
201211s2016 gw | s |||| 0|eng d
020
$a
9783662497227
$9
978-3-662-49722-7
024
7
$a
10.1007/978-3-662-49722-7
$2
doi
035
$a
978-3-662-49722-7
050
4
$a
QA75.5-76.95
072
7
$a
UNH
$2
bicssc
072
7
$a
COM030000
$2
bisacsh
072
7
$a
UNH
$2
thema
072
7
$a
UND
$2
thema
082
0 4
$a
025.04
$2
23
100
1
$a
Knees, Peter.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1108799
245
1 0
$a
Music Similarity and Retrieval
$h
[electronic resource] :
$b
An Introduction to Audio- and Web-based Strategies /
$c
by Peter Knees, Markus Schedl.
250
$a
1st ed. 2016.
264
1
$a
Berlin, Heidelberg :
$b
Springer Berlin Heidelberg :
$b
Imprint: Springer,
$c
2016.
300
$a
XX, 299 p. 82 illus., 47 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
The Information Retrieval Series,
$x
1871-7500 ;
$v
36
505
0
$a
1 Introduction to Music Similarity and Retrieval -- 2 Basic Methods of Audio Signal Processing -- 3 Audio Feature Extraction for Similarity Measurement -- 4 Semantic Labeling of Music -- 5 Contextual Music Meta-data: Comparison and Sources -- 6 Contextual Music Similarity, Indexing, and Retrieval -- 7 Listener-centered Data Sources and Aspects: Traces of Music Interaction -- 8 Collaborative Music Similarity and Recommendation -- 9 Applications -- 10 Grand Challenges and Outlook -- Appendix.
520
$a
This book provides a summary of the manifold audio- and web-based approaches to music information retrieval (MIR) research. In contrast to other books dealing solely with music signal processing, it addresses additional cultural and listener-centric aspects and thus provides a more holistic view. Consequently, the text includes methods operating on features extracted directly from the audio signal, as well as methods operating on features extracted from contextual information, either the cultural context of music as represented on the web or the user and usage context of music. Following the prevalent document-centered paradigm of information retrieval, the book addresses models of music similarity that extract computational features to describe an entity that represents music on any level (e.g., song, album, or artist), and methods to calculate the similarity between them. While this perspective and the representations discussed cannot describe all musical dimensions, they enable us to effectively find music of similar qualities by providing abstract summarizations of musical artifacts from different modalities. The text at hand provides a comprehensive and accessible introduction to the topics of music search, retrieval, and recommendation from an academic perspective. It will not only allow those new to the field to quickly access MIR from an information retrieval point of view but also raise awareness for the developments of the music domain within the greater IR community. In this regard, Part I deals with content-based MIR, in particular the extraction of features from the music signal and similarity calculation for content-based retrieval. Part II subsequently addresses MIR methods that make use of the digitally accessible cultural context of music. Part III addresses methods of collaborative filtering and user-aware and multi-modal retrieval, while Part IV explores current and future applications of music retrieval and recommendation.>.
650
0
$a
Information storage and retrieval.
$3
1069252
650
0
$a
Application software.
$3
528147
650
0
$a
Signal processing.
$3
561459
650
0
$a
Image processing.
$3
557495
650
0
$a
Speech processing systems.
$3
564428
650
0
$a
Big data.
$3
981821
650
1 4
$a
Information Storage and Retrieval.
$3
593926
650
2 4
$a
Computer Appl. in Arts and Humanities.
$3
669937
650
2 4
$a
Signal, Image and Speech Processing.
$3
670837
650
2 4
$a
Big Data/Analytics.
$3
1106909
700
1
$a
Schedl, Markus.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1108800
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783662497203
776
0 8
$i
Printed edition:
$z
9783662497210
776
0 8
$i
Printed edition:
$z
9783662570319
830
0
$a
The Information Retrieval Series,
$x
1871-7500 ;
$v
35
$3
1265345
856
4 0
$u
https://doi.org/10.1007/978-3-662-49722-7
912
$a
ZDB-2-SCS
912
$a
ZDB-2-SXCS
950
$a
Computer Science (SpringerNature-11645)
950
$a
Computer Science (R0) (SpringerNature-43710)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入