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
Statistical humming recognition and ...
~
Shih, Hsuan-Huei.
FindBook
Google Book
Amazon
博客來
Statistical humming recognition and theme finder for query by humming systems.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Statistical humming recognition and theme finder for query by humming systems./
作者:
Shih, Hsuan-Huei.
面頁冊數:
160 p.
附註:
Source: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4538.
Contained By:
Dissertation Abstracts International64-09B.
標題:
Engineering, Electronics and Electrical. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3103968
Statistical humming recognition and theme finder for query by humming systems.
Shih, Hsuan-Huei.
Statistical humming recognition and theme finder for query by humming systems.
- 160 p.
Source: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4538.
Thesis (Ph.D.)--University of Southern California, 2003.
Many people have experience of trying to find a piece of music in music stores, and they only have salient tunes in their mind. Sales people usually have no idea about what the tunes are. However, humming and singing provide the most natural means for content-based retrieval from the music database. In this research, a query by humming system is proposed, and two important components in such a system are examined in this dissertation in detail.Subjects--Topical Terms:
626636
Engineering, Electronics and Electrical.
Statistical humming recognition and theme finder for query by humming systems.
LDR
:03120nmm 2200289 4500
001
1862259
005
20041215100244.5
008
130614s2003 eng d
035
$a
(UnM)AAI3103968
035
$a
AAI3103968
040
$a
UnM
$c
UnM
100
1
$a
Shih, Hsuan-Huei.
$3
1949824
245
1 0
$a
Statistical humming recognition and theme finder for query by humming systems.
300
$a
160 p.
500
$a
Source: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4538.
500
$a
Adviser: Shrikanth Narayanan.
502
$a
Thesis (Ph.D.)--University of Southern California, 2003.
520
$a
Many people have experience of trying to find a piece of music in music stores, and they only have salient tunes in their mind. Sales people usually have no idea about what the tunes are. However, humming and singing provide the most natural means for content-based retrieval from the music database. In this research, a query by humming system is proposed, and two important components in such a system are examined in this dissertation in detail.
520
$a
The first component is a statistical humming recognizer that transcribes what are hummed by people. Statistic speech recognition techniques are used. The segment of a note in the humming waveform is modeled by a hidden Markov model (HMM) while data features such as pitch measures are modeled by a Gaussian mixture model (GMM). Preliminary recognition experiments achieve an overall recognition rate of around 80%.
520
$a
The second component is a theme finder. Themes give highlights of a music piece, and can be used to index music database. Short melodies that repeat many times in a music piece are usually referred as the themes of the music piece. Finding themes is the same as finding repeating melodies in music pieces. A theme indexed music database facilitates the query process. Two dictionary based compression techniques, Lempel Ziv 78 and sliding window techniques, are used to find repeating melodies from music pieces. Experiments performed on a popular music database of MIDI files demonstrate that the proposed algorithms extract repeating melodies effectively with a speed of four times faster than that of the traditional linear search approach.
520
$a
Lastly, advanced humming processing techniques are discussed. Four topics are covered. They include: an enhanced humming recognition technique, music language modeling and its application, a new humming database, and development tools. An expansion of the humming recognition system's structure and the definition of new HMMs note models are experimented. The potential of applying an N-gram based music language model, which is built upon extracted repeating patterns, to the proposed humming recognition system is demonstrated. A humming data collection protocol and development tools are also provided.
590
$a
School code: 0208.
650
4
$a
Engineering, Electronics and Electrical.
$3
626636
690
$a
0544
710
2 0
$a
University of Southern California.
$3
700129
773
0
$t
Dissertation Abstracts International
$g
64-09B.
790
1 0
$a
Narayanan, Shrikanth,
$e
advisor
790
$a
0208
791
$a
Ph.D.
792
$a
2003
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3103968
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
W9180959
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