語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Visualizing Temporality in Music: Mu...
~
Hamidi Ghalehjegh, Nima.
FindBook
Google Book
Amazon
博客來
Visualizing Temporality in Music: Music Perception - Feature Extraction.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Visualizing Temporality in Music: Music Perception - Feature Extraction./
作者:
Hamidi Ghalehjegh, Nima.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
184 p.
附註:
Source: Dissertation Abstracts International, Volume: 79-02(E), Section: A.
Contained By:
Dissertation Abstracts International79-02A(E).
標題:
Music. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10603043
ISBN:
9780355244830
Visualizing Temporality in Music: Music Perception - Feature Extraction.
Hamidi Ghalehjegh, Nima.
Visualizing Temporality in Music: Music Perception - Feature Extraction.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 184 p.
Source: Dissertation Abstracts International, Volume: 79-02(E), Section: A.
Thesis (Ph.D.)--The University of Iowa, 2017.
Recently, there have been efforts to design more efficient ways to internalize music by applying the disciplines of cognition, psychology, temporality, aesthetics, and philosophy. Bringing together the fields of art and science, computational techniques can also be applied to musical analysis. Although a wide range of research projects have been conducted, the automatization of music analysis remains emergent. Importantly, patterns are revealed by using automated tools to analyze core musical elements created from melodies, harmonies, and rhythms, high-level features that are perceivable by the human ear. For music to be captured and successfully analyzed by a computer, however, one needs to extract certain information found in the lower-level features of amplitude, frequency, and duration. Moreover, while the identity of harmonic progressions, melodic contour, musical patterns, and pitch quantification are crucial factors in traditional music analysis, these alone are not exclusive. Visual representations are useful tools that reflect form and structure of non-conventional musical repertoire.
ISBN: 9780355244830Subjects--Topical Terms:
516178
Music.
Visualizing Temporality in Music: Music Perception - Feature Extraction.
LDR
:03087nmm a2200325 4500
001
2158574
005
20180614071648.5
008
190424s2017 ||||||||||||||||| ||eng d
020
$a
9780355244830
035
$a
(MiAaPQ)AAI10603043
035
$a
(MiAaPQ)uiowa:15270
035
$a
AAI10603043
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Hamidi Ghalehjegh, Nima.
$3
3346402
245
1 0
$a
Visualizing Temporality in Music: Music Perception - Feature Extraction.
260
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2017
300
$a
184 p.
500
$a
Source: Dissertation Abstracts International, Volume: 79-02(E), Section: A.
500
$a
Adviser: David Gompper.
502
$a
Thesis (Ph.D.)--The University of Iowa, 2017.
520
$a
Recently, there have been efforts to design more efficient ways to internalize music by applying the disciplines of cognition, psychology, temporality, aesthetics, and philosophy. Bringing together the fields of art and science, computational techniques can also be applied to musical analysis. Although a wide range of research projects have been conducted, the automatization of music analysis remains emergent. Importantly, patterns are revealed by using automated tools to analyze core musical elements created from melodies, harmonies, and rhythms, high-level features that are perceivable by the human ear. For music to be captured and successfully analyzed by a computer, however, one needs to extract certain information found in the lower-level features of amplitude, frequency, and duration. Moreover, while the identity of harmonic progressions, melodic contour, musical patterns, and pitch quantification are crucial factors in traditional music analysis, these alone are not exclusive. Visual representations are useful tools that reflect form and structure of non-conventional musical repertoire.
520
$a
Because I regard the fluidity of music and visual shape as strongly interactive, the ultimate goal of this thesis is to construct a practical tool that prepares the visual material used for musical composition. By utilizing concepts of time, computation, and composition, this tool effectively integrates computer science, signal processing, and music perception. This will be obtained by presenting two concepts, one abstract and one mathematical, that will provide materials leading to the original composition. To extract the desired visualization, I propose a fully automated tool for musical analysis that is grounded in both the mid-level elements of loudness, density, and range, and low-level features of frequency and duration. As evidenced by my sinfonietta, Equilibrium, this tool, capable of rapidly analyzing a variety of musical examples such as instrumental repertoire, electro-acoustic music, improvisation and folk music, is highly beneficial to my proposed compositional procedure.
590
$a
School code: 0096.
650
4
$a
Music.
$3
516178
650
4
$a
Music theory.
$3
547155
650
4
$a
Computer science.
$3
523869
690
$a
0413
690
$a
0221
690
$a
0984
710
2
$a
The University of Iowa.
$b
Music.
$3
1679210
773
0
$t
Dissertation Abstracts International
$g
79-02A(E).
790
$a
0096
791
$a
Ph.D.
792
$a
2017
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10603043
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9358121
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入