東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ null ]

切換: 標籤 | MARC模式 | ISBD

Deep Learning for Large-Scale Harmon...

Sailor, Malcolm,

FindBook

Google Book

Amazon

博客來

Deep Learning for Large-Scale Harmonic Analysis: A Corpus Study of Western Harmony From 1700-1900 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deep Learning for Large-Scale Harmonic Analysis: A Corpus Study of Western Harmony From 1700-1900 // Malcolm Sailor.
作者:	Sailor, Malcolm,
面頁冊數:	1 electronic resource (380 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
Contained By:	Dissertations Abstracts International86-12B.
標題:	Music theory. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31845713
ISBN:	9798286442218

Deep Learning for Large-Scale Harmonic Analysis: A Corpus Study of Western Harmony From 1700-1900 /
Sailor, Malcolm,

Deep Learning for Large-Scale Harmonic Analysis: A Corpus Study of Western Harmony From 1700-1900 /Malcolm Sailor. - 1 electronic resource (380 pages)

Source: Dissertations Abstracts International, Volume: 86-12, Section: B.

This dissertation trains deep learning models for Roman numeral analysis and applies these to the analysis of a corpus of over 12,000 movements of Classical music composed between 1700 and 1900. The Roman numeral analysis models obtain performance that is, as of this writing, state of the art. At the same time, this is the first work of scholarship to employ such models at scale for a music-theoretic corpus study. Consistent with music-historical expectations, this corpus study shows that, along many dimensions, such as the distribution of keys employed or the proportion of chromatic scale degrees, harmonic complexity rose steadily over the study period, while along some other dimensions, such as the transition tendencies of Roman numeral degrees like I and V, harmonic complexity fell before rising again. We also observe that major-key practice changed more than minor-key practice, generally becoming more similar to minor-key practice, and that the usage of keys, scale degrees, and harmonies, tended to become more dispersed over the course of the nineteenth century. Finally, the corpus study reveals some striking symmetries between the modulatory behaviors of major and minor keys.

English

ISBN: 9798286442218Subjects--Topical Terms:

547155
Music theory.
Subjects--Index Terms:

Corpus study

Deep Learning for Large-Scale Harmonic Analysis: A Corpus Study of Western Harmony From 1700-1900 /
LDR:02588nmm a22004213i 4500 001 2433801
005 20250905091016.5
006 m o d
007 cr|nu||||||||
008 261011s2025 miu||||||m |||||||eng d
020 $a 9798286442218
035 $a (MiAaPQD)AAI31845713
035 $a AAI31845713
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Sailor, Malcolm, $e author. $3 3823556
245 1 0 $a Deep Learning for Large-Scale Harmonic Analysis: A Corpus Study of Western Harmony From 1700-1900 / $c Malcolm Sailor.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2025
300 $a 1 electronic resource (380 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
500 $a Advisors: Quinn, Ian Committee members: Cohn, Richard; Frank, Robert.
502 $b Ph.D. $c Yale University $d 2025.
520 $a This dissertation trains deep learning models for Roman numeral analysis and applies these to the analysis of a corpus of over 12,000 movements of Classical music composed between 1700 and 1900. The Roman numeral analysis models obtain performance that is, as of this writing, state of the art. At the same time, this is the first work of scholarship to employ such models at scale for a music-theoretic corpus study. Consistent with music-historical expectations, this corpus study shows that, along many dimensions, such as the distribution of keys employed or the proportion of chromatic scale degrees, harmonic complexity rose steadily over the study period, while along some other dimensions, such as the transition tendencies of Roman numeral degrees like I and V, harmonic complexity fell before rising again. We also observe that major-key practice changed more than minor-key practice, generally becoming more similar to minor-key practice, and that the usage of keys, scale degrees, and harmonies, tended to become more dispersed over the course of the nineteenth century. Finally, the corpus study reveals some striking symmetries between the modulatory behaviors of major and minor keys.
546 $a English
590 $a School code: 0265
650 4 $a Music theory. $3 547155
650 4 $a Musical composition. $3 3289630
653 $a Corpus study
653 $a Harmony
653 $a Machine learning
653 $a Roman numeral analysis
690 $a 0221
690 $a 0800
690 $a 0214
710 2 $a Yale University. $b Music. $e degree granting institution. $3 3823557
720 1 $a Quinn, Ian $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-12B.
790 $a 0265
791 $a Ph.D.
792 $a 2025
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31845713